{"id":"W3209119044","doi":"10.53014/hxnk9240","title":"forWater: Managing Canada’s drinking water from catchment to tap","year":2021,"lang":"en","type":"article","venue":"","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Tap water; Downstream (manufacturing); Drainage basin; Climate change; Water resource management; Environmental science; Resource (disambiguation); Water resources; Environmental planning; Business; Environmental resource management; Natural resource economics; Environmental engineering; Geography; Economics; Computer science; Ecology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001338692,0.0005348909,0.0002306175,0.0009975976,0.007226918,0.004103948,0.001647198,0.001375587,0.007693521],"category_scores_gemma":[0.002084143,0.0002202732,0.0003109584,0.002270636,0.001895924,0.002102659,0.001857056,0.001458294,0.0006686109],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04085382,"about_ca_system_score_gemma":0.1714153,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9864727,"about_ca_topic_score_gemma":0.996104,"domain_scores_codex":[0.9983959,0.0001170804,0.00002328757,0.0001196755,0.0007516035,0.0005924075],"domain_scores_gemma":[0.9979704,0.00009725531,0.00004568766,0.00006275503,0.001068777,0.0007551376],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001062122,0.0001246135,0.0138729,0.0003364599,0.00003844943,0.0005404719,0.004280959,0.003305556,0.006302725,0.03478985,0.6199058,0.3163961],"study_design_scores_gemma":[0.00003139829,0.00007585381,0.01639485,0.0001542074,0.00003004842,0.00008591019,0.008989352,0.003015002,0.003211107,0.006177817,0.9617661,0.00006835928],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1338189,0.01636112,0.03552205,0.2905737,0.003239076,0.00154986,0.01292809,0.00368607,0.5023211],"genre_scores_gemma":[0.5019028,0.01703994,0.07568569,0.02136321,0.000384342,0.0003860872,0.006163819,0.001122363,0.3759518],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.04085382,"threshold_uncertainty_score":0.2964166,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006462776290201095,"score_gpt":0.1920186401261807,"score_spread":0.1855558638359796,"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."}}