{"id":"W4365149291","doi":"10.1515/iupac.94.0638","title":"London Forces","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0004255289,0.0006025156,0.0007374448,0.0001416116,0.0001739747,0.0001728831,0.001255337,0.0008910528,0.007548122],"category_scores_gemma":[0.001694676,0.0005872162,0.0002929379,0.0003111751,0.0001946167,0.00006887985,0.0006284988,0.001694589,0.00006092253],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007490306,"about_ca_system_score_gemma":0.001219506,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006996127,"about_ca_topic_score_gemma":0.001649992,"domain_scores_codex":[0.9955091,0.00002590384,0.0005728772,0.0008137579,0.00219219,0.0008861624],"domain_scores_gemma":[0.9970897,0.0001968011,0.0002599594,0.001624749,0.0004841559,0.0003446523],"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":[0.00008329479,0.0001398185,0.0000106601,0.001726328,0.0001985531,0.0004624016,0.00000689375,0.000005281014,0.0004452906,0.000002105579,0.9957961,0.001123232],"study_design_scores_gemma":[0.0007178407,0.00003992381,0.000001850512,0.000429139,0.00009575515,0.00002784705,0.00004237456,0.0000303914,0.002130453,0.0001553858,0.9957675,0.0005615632],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003670791,0.0005532532,0.000005015594,0.0004064911,0.000308683,0.0001098482,0.9972327,0.0003586811,0.0006582827],"genre_scores_gemma":[0.000005953674,0.001761239,0.00002619153,0.00006358886,0.001920504,0.00003737568,0.9777743,0.0001144524,0.01829642],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.0194584,"threshold_uncertainty_score":0.9996579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02210441936921814,"score_gpt":0.4198166843400091,"score_spread":0.397712264970791,"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."}}