{"id":"W2060325366","doi":"10.1577/1548-8675(2003)023<0078:iuiaut>2.0.co;2","title":"Incorporating Uncertainty into Area-under-the-Curve and Peak Count Salmon Escapement Estimation","year":2003,"lang":"en","type":"article","venue":"North American Journal of Fisheries Management","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"Fisheries and Oceans Canada","funders":"","keywords":"Escapement; Environmental science; Replicate; Oncorhynchus; Fishery; Statistics; Stock assessment; Residence time (fluid dynamics); Count data; Fish <Actinopterygii>; Mathematics; Biology; Geology; Fishing","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":[0.0006967792,0.0001945931,0.0002703579,0.00006319096,0.0004390999,0.00006841656,0.0002398307,0.00001577169,0.0002512125],"category_scores_gemma":[0.00004730317,0.0001457758,0.00005422763,0.000322313,0.0007502966,0.0003106493,0.0002413636,0.0001622535,0.00001452964],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002258352,"about_ca_system_score_gemma":0.00000957873,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001412104,"about_ca_topic_score_gemma":0.003173233,"domain_scores_codex":[0.9985197,0.0001423753,0.0004548293,0.0002232698,0.0004020863,0.0002577702],"domain_scores_gemma":[0.9989395,0.00007707007,0.0006738661,0.0001985035,0.00002795769,0.0000831567],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001090706,0.0001678297,0.8535525,0.0000528597,0.0003843365,0.00006213489,0.001336802,0.0413712,0.000004301354,0.001998042,0.02699334,0.07396762],"study_design_scores_gemma":[0.000465146,0.0006820748,0.9580364,0.00002064969,0.0001475443,0.00001906165,0.007151699,0.0009238121,0.000004924714,0.00256278,0.02974901,0.0002368945],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9717999,0.00003101778,0.008382147,0.00408399,0.0002099638,0.0003365397,0.000001129947,0.00001869994,0.01513664],"genre_scores_gemma":[0.9898457,0.0002003319,0.007819456,0.001832548,0.00001740269,0.00002491828,0.000002669787,0.00001123495,0.0002457174],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1044839,"threshold_uncertainty_score":0.5944566,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007662125824973367,"score_gpt":0.2050406322443561,"score_spread":0.1973785064193828,"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."}}