{"id":"W4400882262","doi":"10.22271/27067483.2023.v5.i2b.275","title":"Evaluating the impact of climate change on water availability and quality","year":2023,"lang":"en","type":"article","venue":"International Journal of Geography Geology and Environment","topic":"Water resources management and optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Climate change; Environmental science; Water resources; Environmental resource management; Natural resource economics; Adaptation (eye); Quality (philosophy); Water quality; Environmental planning; Climate change adaptation; Business; Water resource management; Economics; Ecology","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":[],"consensus_categories":[],"category_scores_codex":[0.0006477511,0.00006510767,0.00009441731,0.0001362681,0.00003120978,0.00001061415,0.00008801257,0.00002752399,0.00007437504],"category_scores_gemma":[0.000006868831,0.00003652338,0.00006784055,0.00002460549,0.00008639006,0.00006484076,0.00006654271,0.00007592113,0.00000501659],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000123445,"about_ca_system_score_gemma":5.502935e-7,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000198277,"about_ca_topic_score_gemma":7.609688e-7,"domain_scores_codex":[0.9994174,0.00005109047,0.0002195063,0.00006058352,0.0001533885,0.00009807074],"domain_scores_gemma":[0.9997885,0.00004825111,0.00006841716,0.00005830728,0.00001512925,0.00002139555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001787343,0.00004040578,0.7435209,0.0000225322,0.0003883818,0.000004975098,0.001038353,0.2251445,0.0007777229,0.00009166455,0.00002214493,0.0287697],"study_design_scores_gemma":[0.0003462647,0.0002573729,0.9847524,0.00001238571,0.00001709376,0.000005201329,0.00004260862,0.01360023,0.0001657534,0.0006144876,0.0001387907,0.00004744705],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9990219,0.0001432296,0.00008374148,0.0003752227,0.0001129524,0.00006187412,0.00000430883,0.000008120418,0.0001886009],"genre_scores_gemma":[0.9970664,0.002770722,0.00006320488,0.00002298,0.00005578211,0.000003702609,0.000006420448,0.000004008413,0.000006803598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2412315,"threshold_uncertainty_score":0.148938,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03844737238374541,"score_gpt":0.3018662835135736,"score_spread":0.2634189111298282,"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."}}