{"id":"W4365149509","doi":"10.1515/iupac.94.0876","title":"Σ-Adduct","year":2023,"lang":"el","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; Chemistry; 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":[0.001387596,0.004406618,0.001840281,0.004058391,0.001740101,0.004092542,0.004025257,0.002853174,0.1470581],"category_scores_gemma":[0.007315319,0.0009108568,0.002323851,0.003864131,0.0006873109,0.00387439,0.003591392,0.003089007,0.3085965],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001408969,"about_ca_system_score_gemma":0.00245823,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01188604,"about_ca_topic_score_gemma":0.02792888,"domain_scores_codex":[0.9979393,0.0003015243,0.0002353464,0.0007639361,0.0004788217,0.0002811057],"domain_scores_gemma":[0.9973592,0.0005077787,0.0001870765,0.001199922,0.0005727069,0.0001733455],"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":[0.0001144232,0.000037264,0.0006292728,0.0005704461,0.00003252385,0.00002827737,0.00001465586,0.0002641354,0.0002274428,0.0006251225,0.9915239,0.005932652],"study_design_scores_gemma":[0.0001962583,0.00004883643,0.002194463,0.0003470379,0.00004295881,0.0001984979,0.00008414328,0.001000705,0.001090947,0.00425188,0.9904978,0.00004645557],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003658123,0.0002880909,0.000455317,0.0001400503,0.0001423865,0.00004020575,0.9911895,0.003744127,0.003634578],"genre_scores_gemma":[0.0004203321,0.00009878573,0.000618769,0.0001301249,0.00001576674,0.00006905201,0.9970706,0.0001986735,0.001377968],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1470581,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03067341928284105,"score_gpt":0.4488655545378979,"score_spread":0.4181921352550568,"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."}}