{"id":"W1491858009","doi":"10.1111/j.1439-0426.2011.01832.x","title":"The use of Dual-frequency IDentification SONar (DIDSON) to document white sturgeon activity in the Columbia River, Canada","year":2011,"lang":"en","type":"article","venue":"Journal of Applied Ichthyology","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":43,"is_retracted":false,"has_abstract":true,"ca_institutions":"ASL Environmental Sciences (Canada); BC Hydro (Canada)","funders":"BC Hydro","keywords":"Sturgeon; Fishery; Acipenser; Lake sturgeon; Biology; Sampling (signal processing); Shore; Population; Environmental science; Fish <Actinopterygii>; Demography; Engineering; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005088632,0.0003137061,0.0001453218,0.001230352,0.0004275978,0.0004280707,0.0005174155,0.0001817216,0.0004067679],"category_scores_gemma":[0.001217899,0.0002959215,0.0000728335,0.000960573,0.0003660416,0.0002726228,0.000378476,0.000193048,0.0001005852],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002609194,"about_ca_system_score_gemma":0.00257778,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.757562,"about_ca_topic_score_gemma":0.9364262,"domain_scores_codex":[0.9996903,0.00002588851,0.00001697195,0.00006761823,0.0001608955,0.00003838969],"domain_scores_gemma":[0.9991642,0.00008719286,0.0001157989,0.00002525398,0.0004982835,0.0001093617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001794681,0.0000632175,0.9167444,0.0000858981,0.00004277592,0.00009522318,0.0003764818,0.0008961097,0.01295356,0.00005101155,0.001117418,0.0673945],"study_design_scores_gemma":[0.00003585046,0.0001176255,0.9915516,0.00002688937,0.00003702762,0.0001013686,0.0002799774,0.004299704,0.002202034,0.00002420377,0.00130349,0.00002006043],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9933509,0.0005389032,0.002468948,0.0000700388,0.00001219381,0.00005465438,0.0008277011,0.00005701299,0.002619675],"genre_scores_gemma":[0.990514,0.0003972386,0.007141357,0.0000492321,0.00000469293,0.00003472166,0.000719592,0.000008018011,0.001131111],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.242438,"threshold_uncertainty_score":0.4877315,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01908183558752804,"score_gpt":0.2054673150222971,"score_spread":0.186385479434769,"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."}}