{"id":"W2794437932","doi":"10.1111/ecog.03498","title":"Box–Cox‐chord transformations for community composition data prior to beta diversity analysis","year":2018,"lang":"en","type":"article","venue":"Ecography","topic":"Community Health and Development","field":"Health Professions","cited_by":100,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Chord (peer-to-peer); Transformation (genetics); Mathematics; Multivariate statistics; Exponent; Statistics; Power transform; Computer science; Discrete mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":["sts"],"consensus_categories":[],"category_scores_codex":[0.002017397,0.0001432336,0.0003207996,0.0007090073,0.01043602,0.00001751107,0.0009719449,0.0001209297,0.0003377997],"category_scores_gemma":[0.00006311457,0.0001456136,0.0001516137,0.001683647,0.00007314042,0.0002942204,0.001013595,0.0006007356,0.0001771052],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000855215,"about_ca_system_score_gemma":0.0001516702,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00240027,"about_ca_topic_score_gemma":0.02628041,"domain_scores_codex":[0.9977715,0.0008394733,0.0004974743,0.0002005136,0.0001982,0.0004928113],"domain_scores_gemma":[0.9969303,0.0008089586,0.0001276765,0.001432492,0.0003499967,0.0003505886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007580736,0.0008773726,0.6322083,0.0007175523,0.001234406,3.578652e-7,0.1069182,0.000009163929,0.00006947548,0.001004152,0.2402025,0.01600038],"study_design_scores_gemma":[0.001158362,0.000276045,0.8004397,0.00007657813,0.0005238591,2.494124e-7,0.006749072,0.0003345115,0.00002971284,0.0008733458,0.189252,0.0002865594],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9122645,0.00004196614,0.06899369,0.007852383,0.0005500293,0.002766714,0.001977605,0.0002147451,0.005338343],"genre_scores_gemma":[0.9720705,0.00002538324,0.01762819,0.007097448,0.0001260213,0.0001349942,0.002851235,0.00001123676,0.00005498829],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1682314,"threshold_uncertainty_score":0.9914874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1824771177291459,"score_gpt":0.4556987965400824,"score_spread":0.2732216788109365,"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."}}