{"id":"W4229842759","doi":"10.1515/iupac.81.0169","title":"Chemisorption","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Environmental Toxicology and Ecotoxicology","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Relation (database); Ecology; Computer science; Biology; Data mining; Philosophy; Linguistics","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":[0.0003915969,0.0003804341,0.0004098602,0.0000585842,0.0001822594,0.00001839782,0.0004895265,0.0007369643,0.193157],"category_scores_gemma":[0.0001352861,0.0003040493,0.0001306673,0.0001320386,0.000603195,0.0001174692,0.0005291557,0.0004598073,0.0002301765],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001134848,"about_ca_system_score_gemma":0.0000414424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003563069,"about_ca_topic_score_gemma":0.0007625684,"domain_scores_codex":[0.9978045,0.00008045894,0.0003561567,0.0006415088,0.0006021836,0.0005151501],"domain_scores_gemma":[0.9988827,0.00006196059,0.0002186894,0.0006503671,0.000007095896,0.0001791858],"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":[0.00006619444,0.0002811239,0.0001450528,0.00001553641,0.00002761031,0.00003603362,0.000003516297,0.000007359401,0.001243606,8.170128e-7,0.9962331,0.001940017],"study_design_scores_gemma":[0.0005427379,0.0002096526,0.0002693689,0.00003417653,0.00004982372,0.00002916609,0.00000477915,0.000001994078,0.0006448172,0.0002460676,0.9975901,0.0003773381],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001682086,0.00006790022,0.00002915545,0.0004411507,0.0005355097,0.000249898,0.995795,0.00004715558,0.001152123],"genre_scores_gemma":[0.00007837282,0.0006651077,0.0000408766,0.0008995603,0.0003446694,0.00003560177,0.9931224,0.00002796902,0.004785451],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1929269,"threshold_uncertainty_score":0.9999412,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009120795609432658,"score_gpt":0.3506952741582462,"score_spread":0.3415744785488135,"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."}}