{"id":"W4235148873","doi":"10.1515/iupac.78.0258","title":"Ecdysone Agonist","year":2016,"lang":"it","type":"dataset","venue":"IUPAC Standards Online","topic":"Neurology and Historical Studies","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Relation (database); Computer science; Pesticide; Ecology; Biology; Data mining","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","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0006827418,0.001098889,0.00157342,0.0003002223,0.001635997,0.0001343239,0.001473343,0.0008310581,0.007937873],"category_scores_gemma":[0.004033606,0.0008437224,0.0004500987,0.0005449248,0.002079843,0.0001825582,0.0009666359,0.001682497,0.0001539225],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009297288,"about_ca_system_score_gemma":0.0008337063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008963011,"about_ca_topic_score_gemma":0.0004543547,"domain_scores_codex":[0.9930423,0.000513721,0.001044496,0.001990248,0.001984735,0.001424515],"domain_scores_gemma":[0.9959099,0.0009347238,0.0006758763,0.001553106,0.0004414202,0.0004850212],"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":[0.000873767,0.000865465,0.00003051037,0.0001536564,0.00008372473,0.001173124,0.00003684674,5.718126e-7,0.0006480921,0.0003021575,0.9931641,0.002667991],"study_design_scores_gemma":[0.001518209,0.001364262,0.0000916594,0.0002154093,0.0002711329,0.00009586047,0.00001003801,0.000002699472,0.0004523389,0.0003797366,0.9946718,0.0009268201],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0003171277,0.002055546,0.0001068717,0.007728788,0.006363707,0.000492101,0.9818883,0.0001647766,0.000882769],"genre_scores_gemma":[0.001589479,0.02435461,0.00003109473,0.008999244,0.005943065,0.00007860678,0.9365838,0.0002214161,0.02219869],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04530452,"threshold_uncertainty_score":0.9996637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02668365401116174,"score_gpt":0.3901846378848609,"score_spread":0.3635009838736992,"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."}}