{"id":"W1597219981","doi":"10.1002/ece3.1614","title":"Environmental effects on survival rates: robust regression, recovery planning and endangered Atlantic salmon","year":2015,"lang":"en","type":"article","venue":"Ecology and Evolution","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bedford Institute of Oceanography; Fisheries and Oceans Canada; Memorial University of Newfoundland","funders":"Fisheries and Oceans Canada","keywords":"Outlier; Overdispersion; Regression; Econometrics; Statistics; Generalized linear model; Population; Regression analysis; Salmo; Geography; Ecology; Mathematics; Biology; Count data; Demography; Fishery; Poisson distribution","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"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":[0.01077018,0.0004340023,0.0003782261,0.0006277176,0.0001636411,0.0005683529,0.0006504457,0.000445712,0.000842416],"category_scores_gemma":[0.02958849,0.0001378176,0.00106282,0.0008767258,0.000638613,0.001131616,0.0006281922,0.0008256178,0.0001430211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006033467,"about_ca_system_score_gemma":0.0005519476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01071907,"about_ca_topic_score_gemma":0.01348126,"domain_scores_codex":[0.9963858,0.00234969,0.0002474345,0.0005676574,0.0003347054,0.0001147661],"domain_scores_gemma":[0.9792194,0.01431107,0.003837718,0.001231218,0.001228023,0.0001727048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006108599,0.0001315898,0.5227063,0.0004844971,0.002512331,0.0004896881,0.0006640712,0.2949887,0.008037543,0.00535736,0.001746903,0.1622702],"study_design_scores_gemma":[0.00001388198,0.0007154516,0.5666659,0.0001219928,0.0005377639,0.0002107551,0.0005156319,0.4176598,0.003189119,0.00799847,0.002253763,0.0001174769],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8918234,0.003225806,0.1002021,0.001380969,0.00005979469,0.00004189789,0.0009254839,0.0004223949,0.001918214],"genre_scores_gemma":[0.9915867,0.0003614569,0.007126923,0.00008891076,0.00001888546,0.00001418064,0.0003533829,0.00006677703,0.0003827698],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01077018,"threshold_uncertainty_score":0.05695879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01448815343834275,"score_gpt":0.2183843861338354,"score_spread":0.2038962326954926,"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."}}