{"id":"W4311557462","doi":"10.1163/9789004322714_cclc_2019-0257-830","title":"New Brunswick Water Resource Report October 2019","year":2022,"lang":"en","type":"dataset","venue":"Climate Change and Law Collection","topic":"Soil and Water Nutrient Dynamics","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Resource (disambiguation); Environmental science; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0002601269,0.0002656882,0.0002544442,0.00006983742,0.0007854846,0.00008621989,0.0001698527,0.0002162727,0.01515735],"category_scores_gemma":[0.000003217187,0.0002138839,0.00007511234,0.0002172043,0.00008100204,0.0001867666,0.0004951196,0.0003042142,0.0002733788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002382136,"about_ca_system_score_gemma":0.00001507552,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04787096,"about_ca_topic_score_gemma":0.006201538,"domain_scores_codex":[0.9983258,0.00006656907,0.0002741303,0.0005799013,0.0003246248,0.0004290313],"domain_scores_gemma":[0.9992964,0.000016167,0.0001255387,0.0004136774,0.000005179143,0.0001430048],"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":[0.0000404343,0.00004008324,0.001475047,0.0000354756,0.00001053387,0.0001254113,0.0002136684,0.000003829401,0.000002916354,0.000009323738,0.9978678,0.0001755201],"study_design_scores_gemma":[0.0002884533,0.0001310444,0.0003845047,0.00001606616,0.00006884882,0.0002897269,0.00002759716,0.00001783984,0.00001938071,0.0002172179,0.9982325,0.0003068013],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.01267224,0.0006024905,0.00000709929,0.001659115,0.003958812,0.001873688,0.9626102,0.000252675,0.01636369],"genre_scores_gemma":[0.00002160828,0.002226314,0.00001638744,0.00080962,0.0004070101,0.00005451886,0.9833657,0.0000320792,0.01306674],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04166942,"threshold_uncertainty_score":0.9857429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01936248126662492,"score_gpt":0.2282149822553471,"score_spread":0.2088525009887222,"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."}}