{"id":"W4237184284","doi":"10.1515/iupac.81.0839","title":"Spawning","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"History and advancements in chemistry","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Environmental risk assessment; Ecology; Computer science; Risk assessment; Biology; Data mining; Philosophy; Linguistics","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":[0.001504005,0.001712512,0.001199224,0.003425539,0.001150123,0.003528609,0.002700955,0.001971034,0.1347115],"category_scores_gemma":[0.01154335,0.0005541946,0.001474698,0.005254057,0.0004350319,0.00252649,0.002579385,0.002236145,0.2258996],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001888249,"about_ca_system_score_gemma":0.003084717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01683362,"about_ca_topic_score_gemma":0.03679785,"domain_scores_codex":[0.9974205,0.0004227895,0.0003220643,0.0009369723,0.0005665788,0.0003310292],"domain_scores_gemma":[0.9959258,0.0008485942,0.0003709187,0.001146048,0.001342046,0.0003666527],"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":[0.000068051,0.00001847439,0.001372268,0.0004413335,0.00001782787,0.00001646275,0.00002169428,0.0001317198,0.00007532587,0.0008362684,0.9921251,0.004875516],"study_design_scores_gemma":[0.00007649169,0.00001198599,0.002598516,0.0003194719,0.00001463853,0.00006120864,0.00007855254,0.0002337523,0.0002099673,0.001509338,0.9948685,0.00001757994],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001759759,0.0001099487,0.0001373578,0.0001461429,0.00006643064,0.00002163514,0.9965528,0.0003293584,0.002460378],"genre_scores_gemma":[0.000384986,0.00006966217,0.0003442992,0.0001112153,0.00001079078,0.00006889664,0.9973321,0.00006083169,0.001617218],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1347115,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01406423731065136,"score_gpt":0.3932291622983936,"score_spread":0.3791649249877422,"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."}}