{"id":"W4233462064","doi":"10.1515/iupac.81.0488","title":"Interspecies Competition","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Ecosystem dynamics and resilience","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Glossary; Ecotoxicology; Environmental risk assessment; Relation (database); Ecology; Computer science; Risk assessment; Biology; Data mining; Linguistics; Philosophy","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003028422,0.000271836,0.0003213018,0.00006084807,0.000116309,0.00005161226,0.0005370151,0.0001969602,0.02392411],"category_scores_gemma":[0.00008954428,0.0001864567,0.0001102476,0.0001210012,0.00028607,0.0001002766,0.000400729,0.0002306376,0.00005976509],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008410914,"about_ca_system_score_gemma":0.00005420908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003113452,"about_ca_topic_score_gemma":0.006196768,"domain_scores_codex":[0.9980207,0.00005433788,0.0003150422,0.0004520228,0.0008443723,0.0003135118],"domain_scores_gemma":[0.9990352,0.0000442576,0.000195261,0.0005672157,0.00003663577,0.0001214703],"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":[0.00001739724,0.00007735693,0.00004915706,0.00003416361,0.00001231543,0.0000240621,0.000008583287,0.00001208965,0.00003396093,0.00002819839,0.9989645,0.0007381988],"study_design_scores_gemma":[0.0002296379,0.00009473946,0.0001703128,0.0002907339,0.00001980214,0.00001493465,0.00003046636,0.00004376668,0.00000591997,0.0001565437,0.9986686,0.0002746013],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0004635485,0.0000840605,0.0003218746,0.0004154263,0.0007176841,0.0001809797,0.9968514,0.00003368761,0.0009312978],"genre_scores_gemma":[0.0004954251,0.0006197176,0.00003707494,0.0001422881,0.0002527541,0.000007801425,0.9973308,0.00001760885,0.001096567],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02386435,"threshold_uncertainty_score":0.9769682,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006023449524543556,"score_gpt":0.3316085172621213,"score_spread":0.3255850677375777,"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."}}