{"id":"W4365147226","doi":"10.1515/iupac.94.0872","title":"Synartetic Acceleration","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; Abandonment (legal); Meaning (existential); 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":[0.001217028,0.004250462,0.002189723,0.002779603,0.001394968,0.003994275,0.004591651,0.002021855,0.1120055],"category_scores_gemma":[0.005786086,0.0008735158,0.002928185,0.004070822,0.0007300503,0.003093089,0.003388078,0.003183707,0.2926577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001138169,"about_ca_system_score_gemma":0.001854815,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01225249,"about_ca_topic_score_gemma":0.03051872,"domain_scores_codex":[0.9982949,0.0003513478,0.00015842,0.0005447823,0.0004085801,0.0002420812],"domain_scores_gemma":[0.9982556,0.0003890192,0.00008072639,0.0008308211,0.0003078053,0.0001360028],"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":[0.000111255,0.00003003024,0.0002819021,0.0004386973,0.00002497651,0.00001976152,0.00002016081,0.0003346089,0.0001265932,0.001032849,0.9922119,0.005367379],"study_design_scores_gemma":[0.0002741993,0.0000435629,0.001251724,0.0002408213,0.00002999805,0.0001240178,0.00005864764,0.002176051,0.001083569,0.006128593,0.9885411,0.00004778147],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0005456423,0.0004848283,0.001098271,0.0001612134,0.0002109358,0.00006279978,0.9665869,0.02286739,0.007982072],"genre_scores_gemma":[0.0007987836,0.0001467636,0.00135918,0.0001070971,0.00001711541,0.0001155303,0.9946998,0.001123876,0.001631856],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1120055,"threshold_uncertainty_score":0.3746958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03106233135663163,"score_gpt":0.4351500752511097,"score_spread":0.404087743894478,"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."}}