{"id":"https://openalex.org/W7222725950","doi":"https://doi.org/10.3389/fmed.2026.1985801","title":"Computational modeling and optimized machine learning for multidrug solubility prediction in supercritical carbon dioxide","display_name":"Computational modeling and optimized machine learning for multidrug solubility prediction in supercritical carbon dioxide","publication_year":2026,"publication_date":"2026-10-16","ids":{"openalex":"https://openalex.org/W7222725950","doi":"https://doi.org/10.3389/fmed.2026.1985801","pmid":"https://pubmed.ncbi.nlm.nih.gov/42964093","pmcid":"https://www.ncbi.nlm.nih.gov/pmc/articles/13719417"},"language":"en","primary_location":{"id":"doi:10.3389/fmed.2026.1985801","doi":"https://doi.org/10.3389/fmed.2026.1985801","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fmed.2026.1985801","pdf_url":"https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2026.1985801/pdf","source":{"id":"https://openalex.org/S2597052008","display_name":"Frontiers in Medicine","issn_l":"2296-858X","issn":["2296-858X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-70","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 Medicine","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/medicine/articles/10.3389/fmed.2026.1985801/pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057811487","display_name":"Nidal H. Abu\u2010Hamdeh","orcid":"https://orcid.org/0000-0002-4852-2217","observed_orcids":["https://orcid.org/0000-0002-4852-2217","https://orcid.org/0000-0001-6380-3810"]},"institutions":[{"id":"https://openalex.org/I185163786","display_name":"King Abdulaziz University","ror":"https://ror.org/02ma4wv74","country_code":"SA","type":"education","lineage":["https://openalex.org/I185163786"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Nidal H. Abu-Hamdeh","raw_affiliation_strings":["Center of Research Excellence in Renewable Energy and Power Systems/Energy Efficiency Group, Department of Mechanical Engineering, Faculty of Engineering, King Abdulaziz University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Center of Research Excellence in Renewable Energy and Power Systems/Energy Efficiency Group, Department of Mechanical Engineering, Faculty of Engineering, King Abdulaziz University","institution_ids":["https://openalex.org/I185163786"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5105033188","display_name":"Hasan H. Hijji","orcid":"https://orcid.org/0000-0001-9977-3000","observed_orcids":["https://orcid.org/0000-0001-9977-3000"]},"institutions":[{"id":"https://openalex.org/I199693650","display_name":"Umm al-Qura University","ror":"https://ror.org/01xjqrm90","country_code":"SA","type":"education","lineage":["https://openalex.org/I199693650"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Hasan H. Hijji","raw_affiliation_strings":["Mechanical Engineering Department, College of Engineering and Architecture, Umm Al-Qura University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Mechanical Engineering Department, College of Engineering and Architecture, Umm Al-Qura University","institution_ids":["https://openalex.org/I199693650"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091854456","display_name":"Khalid H. Almitani","orcid":"https://orcid.org/0000-0001-5155-2225","observed_orcids":["https://orcid.org/0000-0001-5155-2225"]},"institutions":[{"id":"https://openalex.org/I185163786","display_name":"King Abdulaziz University","ror":"https://ror.org/02ma4wv74","country_code":"SA","type":"education","lineage":["https://openalex.org/I185163786"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Khalid H. Almitani","raw_affiliation_strings":["Department of Mechanical Engineering, Faculty of Engineering, King Abdulaziz University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mechanical Engineering, Faculty of Engineering, King Abdulaziz University","institution_ids":["https://openalex.org/I185163786"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5057811487"],"corresponding_institution_ids":["https://openalex.org/I185163786"],"apc_list":{"value":3150,"currency":"CHF","value_usd":3801},"apc_paid":{"value":3150,"currency":"CHF","value_usd":3801},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.66069282,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":null,"first_page":"1985801","last_page":"1985801"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10402","display_name":"Phase Equilibria and Thermodynamics","score":0.8687000274658203,"subfield":{"id":"https://openalex.org/subfields/1606","display_name":"Physical and Theoretical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10402","display_name":"Phase Equilibria and Thermodynamics","score":0.8687000274658203,"subfield":{"id":"https://openalex.org/subfields/1606","display_name":"Physical and Theoretical Chemistry"},"field":{"id":"https://openalex.org/fields/16","display_name":"Chemistry"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10211","display_name":"Computational Drug Discovery Methods","score":0.05119999870657921,"subfield":{"id":"https://openalex.org/subfields/3002","display_name":"Drug Discovery"},"field":{"id":"https://openalex.org/fields/30","display_name":"Pharmacology, Toxicology and Pharmaceutics"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T11881","display_name":"Crystallization and Solubility Studies","score":0.032999999821186066,"subfield":{"id":"https://openalex.org/subfields/2505","display_name":"Materials Chemistry"},"field":{"id":"https://openalex.org/fields/25","display_name":"Materials Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/drug-solubility-prediction","display_name":"drug solubility prediction","score":0.9110000133514404},{"id":"https://openalex.org/keywords/supercritical-carbon-dioxide","display_name":"supercritical carbon dioxide","score":0.9879999756813049},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.6819999814033508},{"id":"https://openalex.org/keywords/few-shot-learning","display_name":"few-shot learning","score":0.7310000061988831},{"id":"https://openalex.org/keywords/molecular-descriptors","display_name":"molecular descriptors","score":0.5170000195503235},{"id":"https://openalex.org/keywords/xgboost","display_name":"XGBoost","score":0.8730000257492065},{"id":"https://openalex.org/keywords/catboost","display_name":"CatBoost","score":0.9940000176429749},{"id":"https://openalex.org/keywords/multilayer-perceptron-regression","display_name":"multilayer perceptron regression","score":0.8790000081062317},{"id":"https://openalex.org/keywords/particle-swarm-optimization","display_name":"particle swarm optimization","score":0.8700000047683716},{"id":"https://openalex.org/keywords/differential-evolution","display_name":"differential evolution","score":0.9110000133514404},{"id":"https://openalex.org/keywords/zero-shot-prediction","display_name":"zero-shot prediction","score":0.492000013589859},{"id":"https://openalex.org/keywords/molecular-weight","display_name":"molecular weight","score":0.5109999775886536},{"id":"https://openalex.org/keywords/melting-point","display_name":"melting point","score":0.9229999780654907},{"id":"https://openalex.org/keywords/temperature-and-pressure-dependence","display_name":"temperature and pressure dependence","score":0.5889999866485596}],"concepts":[{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.6797999739646912},{"id":"https://openalex.org/C132459708","wikidata":"https://www.wikidata.org/wiki/Q744069","display_name":"Extrapolation","level":2,"score":0.6103000044822693},{"id":"https://openalex.org/C155574463","wikidata":"https://www.wikidata.org/wiki/Q170731","display_name":"Solubility","level":2,"score":0.49000000953674316},{"id":"https://openalex.org/C85617194","wikidata":"https://www.wikidata.org/wiki/Q2072794","display_name":"Particle swarm optimization","level":2,"score":0.4830000102519989},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48159998655319214},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.47699999809265137},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.4440999925136566},{"id":"https://openalex.org/C22679943","wikidata":"https://www.wikidata.org/wiki/Q159375","display_name":"Standard deviation","level":2,"score":0.4440000057220459},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.42160001397132874},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3856000006198883},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38100001215934753},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.3806000053882599},{"id":"https://openalex.org/C134458231","wikidata":"https://www.wikidata.org/wiki/Q332582","display_name":"Supercritical carbon dioxide","level":3,"score":0.36550000309944153},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.3257000148296356},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.313400000333786},{"id":"https://openalex.org/C11210021","wikidata":"https://www.wikidata.org/wiki/Q1520713","display_name":"Linearization","level":3,"score":0.2985999882221222},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29589998722076416},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.29440000653266907},{"id":"https://openalex.org/C48921125","wikidata":"https://www.wikidata.org/wiki/Q10861030","display_name":"Linear regression","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.2784999907016754},{"id":"https://openalex.org/C122280245","wikidata":"https://www.wikidata.org/wiki/Q620622","display_name":"Kernel method","level":3,"score":0.27799999713897705},{"id":"https://openalex.org/C186060115","wikidata":"https://www.wikidata.org/wiki/Q30336093","display_name":"Biological system","level":1,"score":0.2768999934196472},{"id":"https://openalex.org/C115901376","wikidata":"https://www.wikidata.org/wiki/Q184199","display_name":"Automation","level":2,"score":0.27570000290870667},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.27000001072883606},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.26269999146461487},{"id":"https://openalex.org/C162040801","wikidata":"https://www.wikidata.org/wiki/Q799897","display_name":"Bootstrap aggregating","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C51989270","wikidata":"https://www.wikidata.org/wiki/Q623738","display_name":"Relative standard deviation","level":3,"score":0.2540000081062317}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.3389/fmed.2026.1985801","doi":"https://doi.org/10.3389/fmed.2026.1985801","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fmed.2026.1985801","pdf_url":"https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2026.1985801/pdf","source":{"id":"https://openalex.org/S2597052008","display_name":"Frontiers in Medicine","issn_l":"2296-858X","issn":["2296-858X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-70","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 Medicine","raw_type":"journal-article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13719417","doi":null,"is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13719417/","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13719417/pdf/fmed-13-1985801.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 Med (Lausanne)","raw_type":"Text"},{"id":"pmid:42964093","doi":null,"is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42964093","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 medicine","raw_type":"Journal Article"},{"id":"pmh:oai:doaj.org/article:08773e66115d4a8ba7ee8db7fd02afc9","doi":null,"is_oa":false,"landing_page_url":"https://doaj.org/article/08773e66115d4a8ba7ee8db7fd02afc9","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 Medicine, Vol 13 (2026)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3389/fmed.2026.1985801","doi":"https://doi.org/10.3389/fmed.2026.1985801","is_oa":true,"landing_page_url":"https://doi.org/10.3389/fmed.2026.1985801","pdf_url":"https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2026.1985801/pdf","source":{"id":"https://openalex.org/S2597052008","display_name":"Frontiers in Medicine","issn_l":"2296-858X","issn":["2296-858X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"listed_in":["cwts-core","doaj","norway-1","poland-70","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 Medicine","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320324047","display_name":"Umm Al-Qura University","ror":"https://ror.org/01xjqrm90"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7222725950.pdf","grobid_xml":"https://content.openalex.org/works/W7222725950.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W1595159159","https://openalex.org/W1965751301","https://openalex.org/W1970010064","https://openalex.org/W1975957241","https://openalex.org/W2008368662","https://openalex.org/W2046033161","https://openalex.org/W2065149084","https://openalex.org/W2068728652","https://openalex.org/W2137983211","https://openalex.org/W2141007997","https://openalex.org/W2152195021","https://openalex.org/W2295598076","https://openalex.org/W2560136348","https://openalex.org/W2565684601","https://openalex.org/W2708474221","https://openalex.org/W2787894218","https://openalex.org/W2949676527","https://openalex.org/W3206176644","https://openalex.org/W4385576721","https://openalex.org/W4390893950","https://openalex.org/W4393353807","https://openalex.org/W4400896653","https://openalex.org/W4401516831","https://openalex.org/W4407418636","https://openalex.org/W4413428296","https://openalex.org/W4415166682","https://openalex.org/W4416291803","https://openalex.org/W7161063267"],"related_works":["https://openalex.org/W4416291803","https://openalex.org/W4415099723","https://openalex.org/W4390893950","https://openalex.org/W7207734233","https://openalex.org/W4414442911","https://openalex.org/W4403042995","https://openalex.org/W4409499222","https://openalex.org/W7165736519","https://openalex.org/W7161063267","https://openalex.org/W7171780083"],"abstract_inverted_index":{")":[0],"is":[1],"complicated":[2],"by":[3,128,166,267],"strong":[4],"compound-specific":[5],"behavior":[6],"and":[7,53,60,63,76,93,104,193,218,247],"response":[8],"values.":[9],"This":[10],"study":[11],"investigated":[12],"whether":[13],"sparse":[14],"measurements":[15],"from":[16,91,212],"a":[17,228,263,269,275],"newly":[18,264],"introduced":[19,265],"drug":[20,266],"can":[21,257],"calibrate":[22,274],"transferable":[23],"machine-learning":[24],"predictions":[25,99],"for":[26,42,149,236,243,262],"computational":[27],"estimation":[28,131,179],"of":[29,34],"solubility":[30],"in":[31],"wide":[32],"range":[33],"parameters.":[35],"A":[36],"curated":[37],"workbook":[38],"containing":[39],"1,618":[40],"observations":[41],"60":[43],"drugs":[44,88],"was":[45,56,125,164],"modeled":[46],"using":[47,70,268],"molecular":[48,245],"weight,":[49],"melting":[50],"point,":[51],"temperature,":[52],"pressure.":[54],"Solubility":[55],"transformed":[57],"as":[58,227],"log\u2081\u2080(S),":[59],"XGBoost,":[61],"CatBoost,":[62],"multilayer":[64],"perceptron":[65],"regression":[66],"were":[67,100,147],"each":[68,96],"tuned":[69],"tree-structured":[71,129],"Parzen":[72,130,178],"estimation,":[73],"differential":[74],"evolution,":[75],"particle":[77],"swarm":[78,168],"optimization.":[79],"Evaluation":[80],"used":[81],"five-fold":[82],"nested":[83],"group":[84],"cross-validation,":[85],"with":[86],"complete":[87],"held":[89],"out":[90],"training":[92],"tuning.":[94],"For":[95],"test":[97],"drug,":[98],"assessed":[101],"before":[102,278],"calibration":[103,156,226],"after":[105],"1,":[106],"3,":[107],"or":[108],"5":[109],"randomly":[110],"selected":[111],"measurements,":[112],"repeated":[113],"ten":[114],"times.":[115],"Within":[116],"the":[117,121,144,160,181,241,259,280],"present":[118],"evaluation":[119],"framework,":[120],"lowest-log-MAE":[122,161],"zero-shot":[123],"configuration":[124],"XGBoost":[126],"optimized":[127],"(log-MAE":[132,170,187,197],"=":[133,136,139,171,174,188,191,198,201,204],"0.584;":[134],"R\u00b2":[135,173,190,200],"-0.087;":[137],"RMSE":[138,203],"1.713":[140],"g/L),":[141],"showing":[142],"that":[143],"four":[145],"descriptors":[146,246],"insufficient":[148],"reliable":[150],"extrapolation":[151],"to":[152,214,273],"unseen":[153,237],"compounds.":[154],"Sparse":[155],"substantially":[157],"improved":[158],"transfer:":[159],"one-shot":[162],"result":[163],"obtained":[165],"CatBoost-particle":[167],"optimization":[169],"0.418;":[172],"0.166),":[175],"whereas":[176],"XGBoost-tree-structured":[177],"had":[180],"lowest":[182],"log-MAE":[183],"at":[184,194],"three":[185],"shots":[186,196],"0.298;":[189],"0.317)":[192],"five":[195,219],"0.251;":[199],"0.452;":[202],"1.223":[205],"g/L).":[206],"Median":[207],"absolute":[208],"relative":[209],"deviation":[210],"decreased":[211],"82.4%":[213],"42.9%":[215],"between":[216],"zero":[217],"shots.":[220],"These":[221],"results":[222],"establish":[223],"sparse,":[224],"leakage-controlled":[225],"more":[229],"defensible":[230],"use":[231],"case":[232],"than":[233],"unconditional":[234],"prediction":[235],"drugs,":[238],"while":[239],"identifying":[240],"need":[242],"richer":[244],"external":[248],"prospective":[249],"validation.":[250],"In":[251],"practical":[252],"terms,":[253],"this":[254],"few-shot":[255],"strategy":[256],"reduce":[258],"experimental":[260],"burden":[261],"small":[270],"screening":[271],"set":[272],"global":[276],"model":[277],"mapping":[279],"remaining":[281],"pressure-temperature":[282],"domain.":[283]},"counts_by_year":[],"updated_date":"2026-11-08T12:12:28.789561","created_date":"2026-10-17T00:00:00"}
