{"id":"W4365149458","doi":"10.1515/iupac.94.0557","title":"Inductive Effect","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); Epistemology; Computer science; 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":[0.002124736,0.003419126,0.001628066,0.00321814,0.002131406,0.003728798,0.003726032,0.002047204,0.197547],"category_scores_gemma":[0.01114887,0.0008032015,0.003526212,0.003208874,0.0007886476,0.003287269,0.003484939,0.003605752,0.2315724],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001820833,"about_ca_system_score_gemma":0.003170742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0126181,"about_ca_topic_score_gemma":0.03743277,"domain_scores_codex":[0.9974729,0.0003902518,0.0001832276,0.001131559,0.0004961012,0.0003258691],"domain_scores_gemma":[0.9958999,0.001640609,0.0001547964,0.001451229,0.000640135,0.0002132858],"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":[0.0001681122,0.00006061719,0.001713495,0.0005899607,0.00005298416,0.00003612407,0.00003325329,0.0004506517,0.0002413917,0.002583233,0.978124,0.01594626],"study_design_scores_gemma":[0.0002195766,0.00004061213,0.003227242,0.0003161943,0.00009025857,0.0001297717,0.00009608881,0.001442401,0.001143597,0.01060966,0.9826382,0.00004648139],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009263372,0.0004510512,0.002823432,0.0003536529,0.0003607689,0.0001430999,0.9728591,0.006073545,0.01600899],"genre_scores_gemma":[0.002213726,0.0002069798,0.004017439,0.0004074117,0.00006100267,0.0003586343,0.9847817,0.0006819646,0.007271081],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.197547,"threshold_uncertainty_score":0.6608604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01958751584180314,"score_gpt":0.4334729638352698,"score_spread":0.4138854479934667,"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."}}