{"id":"W4311548642","doi":"10.1163/9789004322714_cclc_2019-0133-487","title":"Draft 2020 Canada-Ontario Agreement on Great Lakes Water Quality and Ecosystem Health (ERO Number: 019-0198)","year":2022,"lang":"en","type":"dataset","venue":"Climate Change and Law Collection","topic":"Environmental and Social Impact Assessments","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Water quality; Ecosystem; Environmental science; Quality (philosophy); Geography; Environmental protection; Ecology; Biology; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","sts","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003991811,0.000354015,0.0004597526,0.00002289488,0.001505319,0.00009450316,0.0001253085,0.000139651,0.03307753],"category_scores_gemma":[0.000002477149,0.0002978857,0.00005398922,0.00009590545,0.0000824075,0.0001657991,0.0004267527,0.0003392689,0.00006532692],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003811492,"about_ca_system_score_gemma":0.00005309276,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9530507,"about_ca_topic_score_gemma":0.9973929,"domain_scores_codex":[0.9976907,0.0002608083,0.0003746243,0.0005762323,0.0005574027,0.0005401941],"domain_scores_gemma":[0.9992493,0.00003395014,0.0002058419,0.0002507192,0.000003138913,0.0002570375],"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":[0.00005334604,0.0001218945,0.00937385,0.0002100383,0.00003823078,0.00002306342,0.001184323,0.000002449302,0.00001016305,0.000007430514,0.9887235,0.0002517729],"study_design_scores_gemma":[0.0004438706,0.000332169,0.01988862,0.00004883934,0.00004057887,0.00001856803,0.0004400165,0.000003009629,0.00001583357,0.00001973957,0.9783915,0.0003572928],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.1903203,0.0001141912,1.942755e-7,0.001564594,0.001178253,0.001350045,0.8020613,0.0000257574,0.003385359],"genre_scores_gemma":[0.02984819,0.006222955,0.000008919695,0.007995529,0.0003642906,0.0005994233,0.9506707,0.0000528323,0.004237199],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1604721,"threshold_uncertainty_score":0.9999473,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04206668291040565,"score_gpt":0.2894318390458864,"score_spread":0.2473651561354808,"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."}}