{"id":"W4229598363","doi":"10.1515/iupac.78.0221","title":"Concentration-Effect Relationship","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Pesticide and Herbicide Environmental Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Glossary; Relation (database); Chemical nomenclature; Pesticide; Computer science; Management science; Data science; Chemistry; Ecology; Engineering; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001868968,0.001970367,0.002223879,0.007188018,0.0006952715,0.002748027,0.003190599,0.00218948,0.1079707],"category_scores_gemma":[0.0162797,0.0007392925,0.002784961,0.01201465,0.000384191,0.00235525,0.001894119,0.00211953,0.06307156],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002560719,"about_ca_system_score_gemma":0.003626825,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02453539,"about_ca_topic_score_gemma":0.03814705,"domain_scores_codex":[0.9970028,0.0003953298,0.0007610057,0.0009404285,0.0007073843,0.0001930435],"domain_scores_gemma":[0.9917421,0.003653991,0.001389271,0.001172173,0.001801759,0.000240749],"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":[0.0001664223,0.00004335783,0.004067961,0.006926696,0.0002349963,0.00005671573,0.00004072998,0.0006617604,0.0002467409,0.001847414,0.9756873,0.0100199],"study_design_scores_gemma":[0.0001580186,0.00002253103,0.00586085,0.001389675,0.0001294749,0.00009486209,0.00003792865,0.0002411911,0.0002178629,0.00186051,0.9899533,0.00003393229],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000715042,0.0002867411,0.00007614313,0.00005402616,0.00001864607,0.00001795632,0.9987535,0.00007598201,0.0006453869],"genre_scores_gemma":[0.0007798343,0.0005198003,0.0005707106,0.0001708777,0.00001585409,0.0002113207,0.9967331,0.00005505862,0.000943506],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1079707,"threshold_uncertainty_score":0.3611978,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01259126311105773,"score_gpt":0.3572717050116533,"score_spread":0.3446804419005956,"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."}}