{"id":"W3024385857","doi":"10.2307/jj.29010228.11","title":"Distribution and abundance","year":2017,"lang":"en","type":"article","venue":"","topic":"Coccidia and coccidiosis research","field":"Agricultural and Biological Sciences","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Abundance (ecology); Distribution (mathematics); Geography; Mathematics; Biology; Ecology; Mathematical analysis","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.000205143,0.0002361369,0.0002156044,0.003326955,0.0008357633,0.00069867,0.0003106084,0.0001748568,0.007103339],"category_scores_gemma":[0.0004241526,0.0001173022,0.0002833512,0.00202454,0.0003688304,0.0002895805,0.0003707116,0.0002139745,0.001496522],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001394932,"about_ca_system_score_gemma":0.00103411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.3581917,"about_ca_topic_score_gemma":0.5739451,"domain_scores_codex":[0.9996774,0.00001614141,0.00001707209,0.00009699207,0.00009699947,0.0000954492],"domain_scores_gemma":[0.9996088,0.00003042192,0.00009754252,0.00002465078,0.0001564035,0.00008203022],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003169201,0.00006266532,0.7685595,0.0004382972,0.0003618673,0.0003328283,0.002158505,0.000769088,0.03634535,0.001176531,0.01395091,0.1755276],"study_design_scores_gemma":[0.000002420032,0.00001502931,0.990139,0.00001417534,0.0000200789,0.0001932481,0.0003711119,0.0001727884,0.0002901824,0.00005453916,0.008718609,0.000008939644],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9148377,0.004823219,0.001620525,0.0002292926,0.00004436163,0.00009748727,0.03216748,0.0002381943,0.04594174],"genre_scores_gemma":[0.9820419,0.00111061,0.001276258,0.00006537966,0.00002105527,0.00003386429,0.006346951,0.00002540961,0.009078495],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3581917,"threshold_uncertainty_score":0.7122135,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02781281570051628,"score_gpt":0.2683172559273175,"score_spread":0.2405044402268012,"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."}}