{"id":"W4256606732","doi":"10.1515/iupac.88.1157","title":"Osteogenesis","year":2017,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Effects and risks of endocrine disrupting chemicals","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada Research Chairs; University of Toronto","funders":"","keywords":"Glossary; Terminology; Relation (database); Computer science; Linguistics; Data mining; Philosophy","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001271495,0.001317625,0.001389131,0.003868344,0.0008687224,0.002963272,0.002161672,0.001600653,0.119817],"category_scores_gemma":[0.00904392,0.0006959617,0.002003969,0.006533537,0.0003970677,0.001629799,0.002338203,0.001771257,0.09294987],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001064544,"about_ca_system_score_gemma":0.003229036,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01164725,"about_ca_topic_score_gemma":0.03244172,"domain_scores_codex":[0.9985529,0.0002173355,0.0003553995,0.0003730603,0.0003451933,0.0001560551],"domain_scores_gemma":[0.9963091,0.001120277,0.0005626408,0.0009194218,0.0008651959,0.000223358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002198088,0.00002399104,0.003039558,0.005894237,0.00009565143,0.00004696072,0.00005845872,0.0002559125,0.0003442087,0.001209146,0.9680646,0.02074738],"study_design_scores_gemma":[0.0001451153,0.00002058167,0.005750125,0.001675543,0.0000634801,0.0001329753,0.00005868459,0.000100147,0.000246086,0.001368829,0.9904156,0.00002291709],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001679405,0.0005587235,0.0001674735,0.0001111453,0.00005548705,0.00003293612,0.9964067,0.0002455117,0.002253968],"genre_scores_gemma":[0.0006811731,0.0007227166,0.0008533068,0.0002216064,0.00001990781,0.0002111847,0.9954885,0.00009314719,0.001708545],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.119817,"threshold_uncertainty_score":0.4008278,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0123881738096986,"score_gpt":0.4542023250602282,"score_spread":0.4418141512505296,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}