{"id":"W4365147484","doi":"10.1515/iupac.94.0475","title":"Excimer","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":[0.00156305,0.001345703,0.001288482,0.004550317,0.001455201,0.004227802,0.001928619,0.001473794,0.4130397],"category_scores_gemma":[0.01382177,0.0007760116,0.001242872,0.008095277,0.0006916845,0.00380195,0.002934345,0.002778023,0.5461476],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001389096,"about_ca_system_score_gemma":0.001977393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01236799,"about_ca_topic_score_gemma":0.02205128,"domain_scores_codex":[0.9979795,0.0003407737,0.0002683315,0.000580851,0.0005869297,0.0002438135],"domain_scores_gemma":[0.9936777,0.001688086,0.0004241595,0.001975253,0.001941998,0.0002928909],"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":[0.00001440371,0.000003433059,0.0000826533,0.0000871833,0.000002185785,0.00000732634,0.000009288756,0.00001579494,0.00002971815,0.0002837039,0.9967564,0.002707874],"study_design_scores_gemma":[0.00002073858,0.000003722484,0.00068814,0.0001140684,0.000003106419,0.00003485495,0.00004564684,0.00004681947,0.00008542775,0.0006743399,0.9982747,0.000008350186],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002503833,0.0002764733,0.0004465935,0.0008172296,0.0009313188,0.00005861041,0.978353,0.001298661,0.01756781],"genre_scores_gemma":[0.0006079825,0.0002778683,0.0008253357,0.00101683,0.0001994383,0.0002076349,0.9772326,0.0008848464,0.01874735],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4130397,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02749110171906143,"score_gpt":0.4387159379009465,"score_spread":0.4112248361818851,"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."}}