{"id":"W4365147687","doi":"10.1515/iupac.94.0398","title":"Diastereoisomerism","year":2023,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Various Chemistry Research Topics","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Terminology; Meaning (existential); Abandonment (legal); Field (mathematics); Computer science; Epistemology; Linguistics; Philosophy; Mathematics; Political science","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":[0.0008809998,0.003138948,0.001884817,0.003209226,0.001527312,0.002879016,0.002691973,0.001835947,0.09482338],"category_scores_gemma":[0.003147065,0.0007301617,0.002311032,0.004541455,0.0005679281,0.001849602,0.002150962,0.002638499,0.1348515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001448271,"about_ca_system_score_gemma":0.001791606,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0147703,"about_ca_topic_score_gemma":0.03843598,"domain_scores_codex":[0.9988201,0.0001421224,0.0001359117,0.0004497595,0.0002888509,0.0001632498],"domain_scores_gemma":[0.9987286,0.0002716053,0.0001461026,0.0005269697,0.0002249577,0.0001018179],"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":[0.000228408,0.00006879136,0.001193014,0.001595968,0.00006150267,0.00006257095,0.00003090794,0.0004695431,0.001248037,0.001621105,0.9843249,0.00909529],"study_design_scores_gemma":[0.0002522139,0.00006028868,0.005188602,0.000385463,0.00006221889,0.0002824355,0.00007998172,0.0009928531,0.002790536,0.004264487,0.9855689,0.00007197817],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0006606427,0.0004576003,0.000314535,0.00005638285,0.00007210761,0.0000275725,0.9947162,0.0008865786,0.002808257],"genre_scores_gemma":[0.0006681534,0.0001906342,0.0006363983,0.00005253556,0.000008198586,0.00006159169,0.9972315,0.00008661328,0.00106435],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.09482338,"threshold_uncertainty_score":0.3172159,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02515502883787434,"score_gpt":0.4241453997937016,"score_spread":0.3989903709558273,"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."}}