{"id":"W2094043092","doi":"10.1139/f00-003","title":"Determining sampling date interval for precise in situ estimates of cumulative food consumption by fishes","year":2000,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Fish Ecology and Management Studies","field":"Environmental Science","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Lepomis macrochirus; Environmental science; Statistics; Food consumption; Sampling (signal processing); Lepomis; Cumulative effects; Consumption (sociology); Fishery; Cumulative distribution function; Fish consumption; Confidence interval; Ecology; Fish <Actinopterygii>; Mathematics; Biology; Probability density function; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.01303548,0.0003727047,0.0006497279,0.0006302504,0.0004644069,0.00082628,0.0008337895,0.0006003172,0.0003416693],"category_scores_gemma":[0.05668802,0.0004638974,0.0006322445,0.0007665732,0.0004547785,0.0008431785,0.0006735842,0.0004938982,0.0001820959],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005541299,"about_ca_system_score_gemma":0.0005184786,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003310059,"about_ca_topic_score_gemma":0.00661569,"domain_scores_codex":[0.9939516,0.002988574,0.0005803127,0.001041434,0.00127528,0.0001628421],"domain_scores_gemma":[0.9295398,0.05001274,0.0101362,0.004214152,0.005547106,0.0005499221],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002022529,0.0001697323,0.8407292,0.0005017841,0.0005456613,0.0001593671,0.001039032,0.01689103,0.07573763,0.000456263,0.0003762722,0.06137159],"study_design_scores_gemma":[0.00005547054,0.001513536,0.9188368,0.00007682485,0.000372738,0.0004628115,0.0003098427,0.03485804,0.04099735,0.0004448909,0.001997432,0.00007418293],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9032698,0.001228246,0.0931963,0.00008742065,0.00009648922,0.0001037496,0.0004787307,0.000145053,0.001394254],"genre_scores_gemma":[0.9584978,0.0002853547,0.04015061,0.00007734352,0.00004458648,0.0001965286,0.0004960422,0.00005205475,0.0001997477],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01303548,"threshold_uncertainty_score":0.06893903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.044207954739634,"score_gpt":0.2651545497456905,"score_spread":0.2209465950060565,"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."}}