{"id":"https://openalex.org/W7220957674","doi":"https://doi.org/10.3389/frai.2026.1835997","title":"Preprocessing strategies for plant disease instance segmentation: annotation efficiency, context signals, and dual-metric evaluation on PlantSeg","display_name":"Preprocessing strategies for plant disease instance segmentation: annotation efficiency, context signals, and dual-metric evaluation on PlantSeg","publication_year":2026,"publication_date":"2026-10-07","ids":{"openalex":"https://openalex.org/W7220957674","doi":"https://doi.org/10.3389/frai.2026.1835997","pmid":"https://pubmed.ncbi.nlm.nih.gov/42923812","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13688024"},"language":"en","primary_location":{"id":"doi:10.3389/frai.2026.1835997","doi":"https://doi.org/10.3389/frai.2026.1835997","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2026.1835997","pdf_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2026.1835997/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2026.1835997/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5099018864","display_name":"Youssef Natij","orcid":"https://orcid.org/0009-0007-4803-9261","observed_orcids":["https://orcid.org/0009-0007-4803-9261"]},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":true,"raw_author_name":"Youssef Natij","raw_affiliation_strings":["Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018141815","display_name":"Hajar El Karch","orcid":"https://orcid.org/0000-0001-7775-9830","observed_orcids":["https://orcid.org/0000-0001-7775-9830"]},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Hajar El Karch","raw_affiliation_strings":["Laboratory of Advanced Systems Engineering, National School of Applied Sciences, Ibn Tofail University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Laboratory of Advanced Systems Engineering, National School of Applied Sciences, Ibn Tofail University","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120555052","display_name":"Abdelmounaim Belaaribi","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Abdelmounaim Belaaribi","raw_affiliation_strings":["Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5135241009","display_name":"Oumaima Lanaya","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Oumaima Lanaya","raw_affiliation_strings":["Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120363839","display_name":"Meriem El Atik","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Meriem El Atik","raw_affiliation_strings":["Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University","institution_ids":["https://openalex.org/I3121676899"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064529163","display_name":"Abdelkader Mezouari","orcid":"https://orcid.org/0000-0001-5389-2450","observed_orcids":["https://orcid.org/0000-0001-5389-2450"]},"institutions":[{"id":"https://openalex.org/I3121676899","display_name":"Universit\u00e9 Ibn-Tofail","ror":"https://ror.org/02wj89n04","country_code":"MA","type":"education","lineage":["https://openalex.org/I3121676899"]}],"countries":["MA"],"is_corresponding":false,"raw_author_name":"Abdelkader Mezouari","raw_affiliation_strings":["Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Scientific Research and Innovation Laboratory, Higher School of Technology, Ibn Tofail University","institution_ids":["https://openalex.org/I3121676899"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5099018864"],"corresponding_institution_ids":["https://openalex.org/I3121676899"],"apc_list":{"value":1950,"currency":"CHF","value_usd":2353},"apc_paid":{"value":1950,"currency":"CHF","value_usd":2353},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.72120065,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"9","issue":null,"first_page":"1835997","last_page":"1835997"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.001500000013038516,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":9.999999747378752e-05,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/image-preprocessing","display_name":"image preprocessing","score":0.7129999995231628},{"id":"https://openalex.org/keywords/lesion-localization","display_name":"lesion localization","score":0.6430000066757202},{"id":"https://openalex.org/keywords/average-precision","display_name":"average precision","score":0.8240000009536743}],"concepts":[{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.7400000095367432},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6912999749183655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6539999842643738},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6234999895095825},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5760999917984009},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5299999713897705},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4912000000476837},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4641999900341034},{"id":"https://openalex.org/C3019235130","wikidata":"https://www.wikidata.org/wiki/Q188956","display_name":"Plant disease","level":2,"score":0.461899995803833},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.4366999864578247},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4300000071525574},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.4269999861717224},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.38029998540878296},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36570000648498535},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.3497999906539917},{"id":"https://openalex.org/C55166926","wikidata":"https://www.wikidata.org/wiki/Q2892946","display_name":"Oracle","level":2,"score":0.3492000102996826},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3407999873161316},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3366999924182892},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3253999948501587},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.29919999837875366},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.29510000348091125},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.2842999994754791},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2736999988555908},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.27160000801086426},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.263700008392334}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/frai.2026.1835997","doi":"https://doi.org/10.3389/frai.2026.1835997","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2026.1835997","pdf_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2026.1835997/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13688024","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13688024/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13688024/pdf/frai-09-1835997.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Front Artif Intell","raw_type":"Text"},{"id":"pmid:42923812","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42923812","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in artificial intelligence","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:76e24a222bc247f2beaa10ead47d2068","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/76e24a222bc247f2beaa10ead47d2068","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Frontiers in Artificial Intelligence, Vol 9 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/frai.2026.1835997","doi":"https://doi.org/10.3389/frai.2026.1835997","is_oa":true,"landing_page_url":"https://doi.org/10.3389/frai.2026.1835997","pdf_url":"https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2026.1835997/pdf","source":{"id":"https://openalex.org/S4210197006","display_name":"Frontiers in Artificial Intelligence","issn_l":"2624-8212","issn":["2624-8212"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["anvur-class-a","anvur-scientific","cwts-core","doaj","jufo-1","ki-jl-1","norway-1","poland-20","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320527","host_organization_name":"Frontiers Media","host_organization_lineage":["https://openalex.org/P4310320527"],"host_organization_lineage_names":["Frontiers Media"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.40450000762939453,"display_name":"Zero hunger"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7220957674.pdf","grobid_xml":"https://content.openalex.org/works/W7220957674.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2013414890","https://openalex.org/W2085364760","https://openalex.org/W2169768163","https://openalex.org/W2277854822","https://openalex.org/W2339460098","https://openalex.org/W2412782625","https://openalex.org/W2473156356","https://openalex.org/W2731165298","https://openalex.org/W2789255992","https://openalex.org/W2790979755","https://openalex.org/W2804860796","https://openalex.org/W2911433502","https://openalex.org/W2913500366","https://openalex.org/W2989646980","https://openalex.org/W3027763298","https://openalex.org/W3130071898","https://openalex.org/W4281695711","https://openalex.org/W4322740557","https://openalex.org/W4386952528","https://openalex.org/W4387879624","https://openalex.org/W4391451930","https://openalex.org/W4406627155","https://openalex.org/W7116986643","https://openalex.org/W7118092676","https://openalex.org/W7128430662","https://openalex.org/W7133196671"],"related_works":["https://openalex.org/W7166097098","https://openalex.org/W7167888122","https://openalex.org/W4417249326","https://openalex.org/W7160168332","https://openalex.org/W3204309289","https://openalex.org/W7172278731","https://openalex.org/W4319879411","https://openalex.org/W7220857282","https://openalex.org/W4408290725","https://openalex.org/W7211965781"],"abstract_inverted_index":{"Preprocessing":[0],"choices":[1],"can":[2,155],"strongly":[3],"affect":[4],"how":[5],"well":[6],"segmentation":[7,19,34,219],"models":[8],"localize":[9],"disease":[10,33,39,208],"lesions":[11],"in":[12,206],"field":[13],"imagery,":[14],"but":[15],"no":[16],"systematic":[17,217],"instance":[18,196,218],"study":[20,220],"has":[21],"yet":[22],"been":[23],"reported":[24],"on":[25,64,140,150,221],"PlantSeg,":[26,222],"the":[27,91,110,125,129,168,171,177,183,215],"largest":[28],"publicly":[29,230],"available":[30],"in-the-wild":[31],"plant":[32,43,207],"dataset":[35],"(11,458":[36],"images;":[37],"115":[38],"categories;":[40],"34":[41],"host":[42],"species).":[44],"We":[45],"evaluated":[46],"six":[47],"preprocessing":[48,96],"strategies,":[49],"ranging":[50],"from":[51,136],"annotation-free":[52],"baselines":[53],"to":[54],"expert":[55],"polygon-guided":[56],"approaches,":[57],"each":[58],"trained":[59],"for":[60,109,203],"approximately":[61],"11.5":[62],"h":[63],"a":[65],"single":[66],"NVIDIA":[67],"A100":[68],"GPU,":[69],"and":[70,80,83,100,107,119,121,173,195,223,226],"assessed":[71],"them":[72],"with":[73,105],"pixel-level":[74,120],"mean":[75],"intersection":[76],"over":[77],"union":[78],"(mIoU)":[79],"instance-level":[81,122],"bounding-box":[82],"mask":[84,102,114],"average":[85],"precision":[86],"(AP).":[87],"Annotation-guided":[88],"cropping":[89],"gave":[90],"strongest":[92],"results:":[93],"bounding":[94],"box-guided":[95],"reached":[97],"34.12%":[98],"mIoU":[99],"13.34%":[101],"mAP50,":[103],"compared":[104],"27.93%":[106],"10.07%":[108],"unprocessed":[111],"baseline.":[112],"Context-aware":[113],"augmentation":[115,166],"consistently":[116],"degraded":[117],"performance,":[118],"metrics":[123],"ranked":[124],"strategies":[126],"differently.":[127],"Because":[128],"annotation-guided":[130],"conditions":[131],"derive":[132],"their":[133],"crop":[134],"windows":[135],"ground-truth":[137],"lesion":[138],"locations":[139],"every":[141],"split,":[142],"these":[143],"gains":[144],"represent":[145],"an":[146,158],"oracle":[147],"upper":[148],"bound":[149],"what":[151],"disease-aware":[152],"spatial":[153],"guidance":[154],"contribute,":[156],"not":[157],"end-to-end":[159],"deployable":[160],"pipeline.":[161],"The":[162,187],"degradation":[163],"under":[164],"context-aware":[165],"supports":[167],"hypothesis":[169],"that":[170],"color":[172],"texture":[174],"contrast":[175],"at":[176],"healthy-to-necrotic":[178],"boundary":[179],"carries":[180],"diagnostic":[181],"signal":[182],"model":[184],"actively":[185],"exploits.":[186],"divergent":[188],"metric":[189],"rankings":[190],"arise":[191],"because":[192],"semantic":[193],"overlap":[194],"matching":[197],"capture":[198],"complementary":[199],"properties,":[200],"which":[201],"argues":[202],"dual-metric":[204],"reporting":[205],"segmentation.":[209],"To":[210],"our":[211],"knowledge,":[212],"this":[213],"is":[214],"first":[216],"all":[224],"code":[225],"per-instance":[227],"predictions":[228],"are":[229],"released.":[231]},"counts_by_year":[],"updated_date":"2026-10-29T09:56:32.521200","created_date":"2026-10-09T00:00:00"}