{"id":"W4233057520","doi":"10.1515/iupac.76.0388","title":"Stereoselectivity","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; Toxicokinetics; Hazard; Relation (database); Computer science; Toxicology; Medicine; Chemistry; Pharmacology; Data mining; Biology; 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":[0.001473937,0.002532664,0.00170094,0.00540055,0.001189197,0.003640327,0.002607819,0.001839813,0.1126416],"category_scores_gemma":[0.009542366,0.0008338328,0.002322181,0.006952672,0.0005856859,0.002761269,0.002602456,0.002265906,0.1218425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001873843,"about_ca_system_score_gemma":0.00314387,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01685838,"about_ca_topic_score_gemma":0.03413447,"domain_scores_codex":[0.9975036,0.0003223427,0.0004557475,0.0008577971,0.0006249326,0.0002356453],"domain_scores_gemma":[0.9954717,0.00144963,0.0005763131,0.001200199,0.001032105,0.0002701614],"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":[0.0001940638,0.00004637625,0.002250398,0.002815784,0.00006158233,0.00004509715,0.00006460054,0.0003616955,0.0005241162,0.001528272,0.9820093,0.01009863],"study_design_scores_gemma":[0.0001336547,0.00002171109,0.004808878,0.0005989138,0.00003897849,0.00009162511,0.00007351943,0.0002408601,0.0005968945,0.001666997,0.9916889,0.00003911777],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001983257,0.0002176275,0.0001271681,0.00004457978,0.00002904245,0.0000206165,0.9975621,0.0003861941,0.001414369],"genre_scores_gemma":[0.0004166358,0.0001415886,0.0004475432,0.00006895523,0.000007897808,0.00009862809,0.9978938,0.0001050312,0.0008199697],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1126416,"threshold_uncertainty_score":0.3768235,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01368174603507881,"score_gpt":0.3890077837603795,"score_spread":0.3753260377253007,"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."}}