{"id":"W4250229180","doi":"10.1515/iupac.81.0784","title":"Risk Hypotheses (in Ecological Risk Assessment)","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Chemistry and Chemical Engineering","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); Risk assessment; Ecology; Computer science; Biology; Data mining; 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":[0.0005342663,0.0003897816,0.0004664863,0.00003491368,0.00008111537,0.00003483501,0.0005351966,0.0004392077,0.02579087],"category_scores_gemma":[0.001039098,0.0002874418,0.0001463352,0.0001651294,0.0002138412,0.00009086898,0.0004095582,0.0009944385,0.00001362703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001169227,"about_ca_system_score_gemma":0.00007095424,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002538135,"about_ca_topic_score_gemma":0.0005701704,"domain_scores_codex":[0.9976885,0.00006978138,0.0004109856,0.0006103612,0.0007325549,0.0004878145],"domain_scores_gemma":[0.9986982,0.0003047201,0.0002273603,0.0005672234,0.00001492914,0.000187621],"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":[0.00003088117,0.0002896523,0.002450413,0.00002829102,0.00002407169,0.00005965036,0.000002499325,0.0002729591,0.000359479,3.220962e-7,0.994203,0.002278728],"study_design_scores_gemma":[0.0005911349,0.00006199731,0.005275476,0.00008885504,0.00005652107,0.000005999205,0.00000676191,0.000099517,0.0003059637,0.0002947507,0.9927953,0.000417759],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.02405489,0.00005729686,0.00008844811,0.0000650842,0.0001393623,0.0001349842,0.9748511,0.00005125364,0.0005576247],"genre_scores_gemma":[0.004750234,0.001933638,0.000263033,0.00006709155,0.0003482448,0.00002879576,0.9923078,0.00003134366,0.0002697534],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02577724,"threshold_uncertainty_score":0.9999578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007013111492540228,"score_gpt":0.3352480614377308,"score_spread":0.3282349499451906,"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."}}