{"id":"W4365147214","doi":"10.1515/iupac.94.0654","title":"Meisenheimer Adduct","year":2023,"lang":"de","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; Chemistry; Computer science; Linguistics; Philosophy; Mathematics; Political science; Law","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":[0.00129298,0.002759161,0.001782557,0.003710051,0.001391942,0.004685828,0.003023439,0.00185269,0.153504],"category_scores_gemma":[0.007059739,0.0007528347,0.001716259,0.004736172,0.0005722531,0.003179017,0.003086061,0.002521734,0.3723133],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001198393,"about_ca_system_score_gemma":0.002024441,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0114886,"about_ca_topic_score_gemma":0.02856174,"domain_scores_codex":[0.998087,0.0003206666,0.0002151745,0.0006831365,0.0004259338,0.0002681596],"domain_scores_gemma":[0.9978294,0.0004450455,0.0001771073,0.0009640347,0.0004167812,0.0001676275],"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":[0.00008628786,0.0000197411,0.0005233621,0.0004181729,0.0000223776,0.00001812852,0.00002219162,0.0001608459,0.0001309306,0.0009851321,0.9900306,0.007582236],"study_design_scores_gemma":[0.00008869531,0.000017283,0.001782698,0.0002562006,0.00001950785,0.0000769008,0.00005749643,0.0004348249,0.0004275982,0.003058497,0.9937527,0.00002770381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003179444,0.0003126007,0.0004097851,0.0001415272,0.0001239374,0.00003379695,0.991303,0.001776806,0.005580574],"genre_scores_gemma":[0.0005692929,0.0001612541,0.0006794577,0.0001033028,0.0000208568,0.0000911104,0.9954315,0.0002902812,0.002652959],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.153504,"threshold_uncertainty_score":0.5135221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03180148027025453,"score_gpt":0.4397016101468451,"score_spread":0.4079001298765905,"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."}}