{"id":"W1970196155","doi":"10.1007/s00300-014-1533-7","title":"Statistical power: an important consideration in designing community-based monitoring programs for Arctic and sub-Arctic subsistence fisheries","year":2014,"lang":"en","type":"article","venue":"Polar Biology","topic":"Marine and fisheries research","field":"Environmental Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba; Fisheries and Oceans Canada","funders":"National Academy of Sciences of Ukraine","keywords":"Statistical power; Biology; Sample size determination; Arctic; Population; Fecundity; Metric (unit); Statistics; Stock assessment; Sample (material); Fishing; Ecology; Engineering; Mathematics; Operations management; Demography","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":[0.0009017756,0.00009669993,0.000143323,0.00003000173,0.0002116894,0.00005738133,0.0001132851,0.00007515855,0.00008856271],"category_scores_gemma":[0.0004779885,0.00008896452,0.00001430625,0.00007671712,0.0004258042,0.0001169474,0.00008610928,0.0002214936,0.00000243249],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005984182,"about_ca_system_score_gemma":0.00001478856,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00338389,"about_ca_topic_score_gemma":0.002363337,"domain_scores_codex":[0.9987643,0.0004593035,0.0001982166,0.0001987047,0.00007357127,0.0003058522],"domain_scores_gemma":[0.9991968,0.0004726411,0.00004413932,0.0001798814,0.00001595658,0.00009056662],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00005390204,0.00005858428,0.9821274,0.00003198208,0.000002791547,0.000001608229,0.0001828216,0.000001491205,0.006427169,0.0003430922,0.000002662578,0.01076654],"study_design_scores_gemma":[0.0007049285,0.001936977,0.9815652,0.00001596475,0.000009592673,0.0000136365,0.0004307973,0.003521572,0.001975378,0.006080233,0.003483851,0.0002619113],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898764,0.000009733971,0.009073189,0.0001977747,0.00004831062,0.0003206728,0.000006570575,0.00002127197,0.0004460779],"genre_scores_gemma":[0.9878969,0.00000838135,0.01181814,0.00009787986,0.00001545561,0.00006950679,0.0000787489,0.000009478952,0.000005463839],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01050462,"threshold_uncertainty_score":0.5115452,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04394204819293807,"score_gpt":0.2964902437253038,"score_spread":0.2525481955323657,"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."}}