{"id":"W4252780756","doi":"10.1079/9781845932756.0251","title":"Analysis of variance: testing differences between several means.","year":2019,"lang":"en","type":"book-chapter","venue":"CABI eBooks","topic":"Forest ecology and management","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Statistics; Variance (accounting); Analysis of variance; One-way analysis of variance; Acronym; Sampling (signal processing); Mathematics; Population variance; Computer science; Linguistics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.005098055,0.001665516,0.001382935,0.003048646,0.0005938672,0.0024896,0.001710045,0.00134478,0.02426825],"category_scores_gemma":[0.01013225,0.0003704805,0.000814234,0.003616092,0.001594861,0.002753987,0.001607488,0.002211924,0.01437465],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009019197,"about_ca_system_score_gemma":0.001768834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008273508,"about_ca_topic_score_gemma":0.00105448,"domain_scores_codex":[0.9940113,0.001783461,0.000308426,0.0007545462,0.003048448,0.00009373148],"domain_scores_gemma":[0.9936808,0.004425891,0.0004687787,0.0004731082,0.0008239053,0.0001275119],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001227648,0.0001484208,0.001564374,0.003798482,0.0003105693,0.0002240461,0.0009802782,0.001308551,0.009019868,0.04325062,0.1628575,0.7764146],"study_design_scores_gemma":[0.0000249787,0.0002710136,0.00382152,0.001396278,0.0001140485,0.0005206089,0.0003283437,0.001460673,0.003065804,0.05240649,0.9365196,0.00007074857],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.006526683,0.09915905,0.6908664,0.005532132,0.01092442,0.001426057,0.007438084,0.008349495,0.1697778],"genre_scores_gemma":[0.03633364,0.09832817,0.7742954,0.004827085,0.003899176,0.00373578,0.009157076,0.00357822,0.06584549],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02426825,"threshold_uncertainty_score":0.08118534,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02462740274536098,"score_gpt":0.2146310774206465,"score_spread":0.1900036746752855,"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."}}