{"id":"https://openalex.org/W7108340352","doi":"https://doi.org/10.5281/zenodo.17782497","title":"Toward Predictive Anomalous Systems Analysis (pASA): Domain Trends, Drift Forecasting, Cascade Modeling, and Spatial Probability in the Unified Archetypal Bayesian Theory","display_name":"Toward Predictive Anomalous Systems Analysis (pASA): Domain Trends, Drift Forecasting, Cascade Modeling, and Spatial Probability in the Unified Archetypal Bayesian Theory","publication_year":2025,"publication_date":"2025-12-01","ids":{"openalex":"https://openalex.org/W7108340352","doi":"https://doi.org/10.5281/zenodo.17782497"},"language":"en","primary_location":{"id":"doi:10.5281/zenodo.17782497","doi":"https://doi.org/10.5281/zenodo.17782497","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17782497","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.5281/zenodo.17782497","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5121717262","display_name":"Zachariah Laing","orcid":"https://orcid.org/0009-0004-8765-4601","observed_orcids":["https://orcid.org/0009-0004-8765-4601"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Laing, Zachariah","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0004-8765-4601","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5121717262"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8428000211715698,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.8428000211715698,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T14345","display_name":"Scientific Research and Philosophical Inquiry","score":0.01209999993443489,"subfield":{"id":"https://openalex.org/subfields/1405","display_name":"Management of Technology and Innovation"},"field":{"id":"https://openalex.org/fields/14","display_name":"Business, Management and Accounting"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13141","display_name":"Statistical Methods and Applications","score":0.011099999770522118,"subfield":{"id":"https://openalex.org/subfields/2613","display_name":"Statistics and Probability"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/spatial-probability","display_name":"spatial probability","score":0.6809999942779541},{"id":"https://openalex.org/keywords/anomaly-classification","display_name":"anomaly classification","score":0.38600000739097595}],"concepts":[{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6359999775886536},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5964000225067139},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5651000142097473},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5360000133514404},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5250999927520752},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.477400004863739},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.46880000829696655},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4681999981403351},{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.4657999873161316},{"id":"https://openalex.org/C917703","wikidata":"https://www.wikidata.org/wiki/Q7239668","display_name":"Predictive inference","level":5,"score":0.4562000036239624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4429999887943268},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.39089998602867126},{"id":"https://openalex.org/C43169469","wikidata":"https://www.wikidata.org/wiki/Q580922","display_name":"Preprint","level":2,"score":0.3847000002861023},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.3650999963283539},{"id":"https://openalex.org/C101112237","wikidata":"https://www.wikidata.org/wiki/Q4874481","display_name":"Bayesian statistics","level":4,"score":0.3644999861717224},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.350600004196167},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.34529998898506165},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C64848388","wikidata":"https://www.wikidata.org/wiki/Q188867","display_name":"Futures studies","level":2,"score":0.305400013923645},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.3034999966621399},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C55689738","wikidata":"https://www.wikidata.org/wiki/Q15963867","display_name":"Discrete time and continuous time","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.29319998621940613},{"id":"https://openalex.org/C43596424","wikidata":"https://www.wikidata.org/wiki/Q98124957","display_name":"Probability and statistics","level":2,"score":0.2705000042915344},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.27000001072883606},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26930001378059387},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26600000262260437},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2572999894618988}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.5281/zenodo.17782497","doi":"https://doi.org/10.5281/zenodo.17782497","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17782497","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},{"id":"doi:10.5281/zenodo.17782498","doi":"https://doi.org/10.5281/zenodo.17782498","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17782498","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.5281/zenodo.17782497","doi":"https://doi.org/10.5281/zenodo.17782497","is_oa":true,"landing_page_url":"https://doi.org/10.5281/zenodo.17782497","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W7104256814","https://openalex.org/W7104055137","https://openalex.org/W2562975557","https://openalex.org/W7098739436","https://openalex.org/W7134122365","https://openalex.org/W1650679371","https://openalex.org/W3009371684","https://openalex.org/W2181807144","https://openalex.org/W7014725932","https://openalex.org/W2549640698"],"abstract_inverted_index":{"Through":[0],"analytical":[1],"examples,":[2],"mathematically":[3],"grounded":[4],"proofs-of-concept,":[5],"and":[6,14,70,90],"multi-layered":[7],"integration":[8],"of":[9,24],"NOAA,":[10],"NASA,":[11],"USGS,":[12],"anthropological,":[13],"institutional":[15],"datasets,":[16],"this":[17],"preprint":[18],"demonstrates":[19],"that":[20],"ASA":[21,39],"is":[22,77,81],"capable":[23],"meaningful":[25],"forward-looking":[26],"inference":[27],"at":[28],"multiple":[29],"scales\u2014from":[30],"regional":[31],"archaeological":[32],"likelihoods":[33],"to":[34],"cross-domain":[35],"activation":[36,68],"sequences.":[37],"Predictive":[38],"moves":[40],"anomaly":[41],"science":[42],"from":[43],"classification":[44],"into":[45],"early-stage":[46],"forecasting.":[47],"It":[48],"does":[49,59],"not":[50,78],"predict":[51],"discrete":[52],"events":[53],"with":[54],"absolute":[55],"specificity,":[56],"but":[57],"it":[58,80],"generate":[60],"statistically":[61],"significant":[62],"foresight":[63],"about":[64],"event":[65],"classes,":[66],"domain":[67],"cycles,":[69],"spatiotemporal":[71],"APC":[72],"likelihood":[73],"fields.":[74],"This":[75],"capability":[76],"speculative;":[79],"built":[82],"directly":[83],"upon":[84],"the":[85],"data":[86],"structures,":[87],"equations,":[88],"ecosystem,":[89],"methodology":[91],"already":[92],"validated":[93],"within":[94],"ASA.":[95]},"counts_by_year":[],"updated_date":"2026-11-13T13:42:25.865203","created_date":"2025-12-03T00:00:00"}