{"id":"W2087784353","doi":"10.1139/f04-051","title":"Variance heterogeneity, transformations, and models of species abundance: a cautionary tale","year":2004,"lang":"en","type":"article","venue":"Canadian Journal of Fisheries and Aquatic Sciences","topic":"Ecology and Vegetation Dynamics Studies","field":"Environmental Science","cited_by":67,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Statistics; Econometrics; Homogeneity (statistics); Variance (accounting); Nonparametric statistics; Mathematics; Spatial heterogeneity; Statistical hypothesis testing; Abundance (ecology); Type I and type II errors; Ecology; Biology","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.02029942,0.001599379,0.002273417,0.002225408,0.002068932,0.005520829,0.008558124,0.006499215,0.004747089],"category_scores_gemma":[0.1084686,0.001043995,0.002501616,0.003435811,0.01383042,0.01571441,0.004084351,0.02951452,0.002401797],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001709059,"about_ca_system_score_gemma":0.001534123,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0109323,"about_ca_topic_score_gemma":0.00933359,"domain_scores_codex":[0.9921452,0.004605021,0.0006308687,0.0009087861,0.001535514,0.0001745049],"domain_scores_gemma":[0.9201794,0.06564441,0.001697498,0.007480526,0.004260526,0.0007375836],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001088843,0.00005550652,0.003255629,0.0005629088,0.0003680004,0.001165441,0.001626011,0.008658074,0.0002399098,0.7177902,0.2217641,0.04440524],"study_design_scores_gemma":[0.00001683318,0.00001836152,0.0004325661,0.000159164,0.00002854262,0.0004224691,0.0002114022,0.007072764,0.00007480953,0.9357679,0.05574825,0.00004695989],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"methods","genre_scores_codex":[0.00527843,0.05180085,0.3729896,0.5292487,0.02027163,0.0001481304,0.001000712,0.00100691,0.01825508],"genre_scores_gemma":[0.2247503,0.05335158,0.3206191,0.2404448,0.1047844,0.001095456,0.0008316237,0.001604214,0.05251867],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9797006,"threshold_uncertainty_score":0.1073549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01747347594291337,"score_gpt":0.2140102531159622,"score_spread":0.1965367771730488,"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."}}