{"id":"W2479353618","doi":"","title":"Exploring Resilience of Canadian Rivers to Climate Change","year":2015,"lang":"en","type":"article","venue":"AGU Fall Meeting Abstracts","topic":"Hydrology and Watershed Management Studies","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Climate change; Resilience (materials science); Environmental resource management; Environmental science; Environmental planning; Geography; Geology; Oceanography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.001101342,0.000328993,0.0002403656,0.001310709,0.003098191,0.002715697,0.0008467407,0.000597394,0.002949505],"category_scores_gemma":[0.005340879,0.0001877758,0.0005432294,0.002523858,0.001790083,0.001009651,0.00127533,0.000784494,0.0001022346],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0323586,"about_ca_system_score_gemma":0.02900092,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9897583,"about_ca_topic_score_gemma":0.9942532,"domain_scores_codex":[0.9995517,0.00006597069,0.0000122048,0.00008322505,0.00007892389,0.0002079814],"domain_scores_gemma":[0.998421,0.0004776441,0.0001779331,0.0001134241,0.0005599915,0.0002500573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002832308,0.00009933711,0.804495,0.0001458138,0.000438363,0.0004369762,0.008034043,0.08752174,0.003328358,0.02530647,0.006821298,0.06308933],"study_design_scores_gemma":[0.00001191218,0.00005123315,0.9314688,0.00008391772,0.0002136407,0.00005769188,0.017399,0.02789301,0.0008926877,0.009708357,0.01214929,0.00007032636],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9836913,0.0002563112,0.0006569728,0.001391062,0.000007735249,0.00002103299,0.0008599546,0.00002431303,0.01309128],"genre_scores_gemma":[0.997959,0.0002113864,0.0004860111,0.00005784132,0.000002390483,0.000008151999,0.0002530135,0.000007303182,0.001014949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0323586,"threshold_uncertainty_score":0.2347792,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09467535253323804,"score_gpt":0.2462102855713725,"score_spread":0.1515349330381345,"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."}}