{"id":"W2022148426","doi":"10.1111/jeb.12486","title":"Adaptive landscape and functional diversity of Neotropical cichlids: implications for the ecology and evolution of Cichlinae (Cichlidae; Cichliformes)","year":2014,"lang":"en","type":"article","venue":"Journal of Evolutionary Biology","topic":"Fish biology, ecology, and behavior","field":"Environmental Science","cited_by":63,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Ontario Museum; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; University of California, Davis; Academy of Natural Sciences of Drexel University; University of Toronto; Royal Ontario Museum","keywords":"Biology; Cichlid; Ecology; Null model; Ecomorphology; Evolutionary biology; Trait; Adaptation (eye); Evolutionary ecology; Convergent evolution; Functional ecology; Lineage (genetic); Functional diversity; Phylogenetics; Ecosystem; Habitat","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008149069,0.0002418864,0.0002783471,0.001256765,0.000302857,0.0006439452,0.0002850468,0.0003125535,0.0007652223],"category_scores_gemma":[0.002378689,0.0001454694,0.0002791846,0.0007685478,0.0006365955,0.0004509707,0.0005366563,0.0002936118,0.00008392159],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004978981,"about_ca_system_score_gemma":0.0002277219,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005752823,"about_ca_topic_score_gemma":0.008265408,"domain_scores_codex":[0.9998001,0.00006174132,0.0000168486,0.00006809108,0.00003377581,0.00001949814],"domain_scores_gemma":[0.9992037,0.0003289923,0.0001629337,0.00008394901,0.0001409591,0.00007949315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001141808,0.000028042,0.9444929,0.0001116676,0.0002501763,0.0001005625,0.0008934596,0.007172362,0.0171527,0.0006284078,0.0001557817,0.02889984],"study_design_scores_gemma":[0.000002505806,0.00001087635,0.9903029,0.000004881437,0.0000140332,0.00005681143,0.0001281432,0.008842944,0.0001495725,0.0003651733,0.0001162448,0.00000597683],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988552,0.0001866338,0.0006144033,0.00002586343,7.097649e-7,0.000002786631,0.00008186448,0.000007595247,0.0002249588],"genre_scores_gemma":[0.998955,0.00005402135,0.0007723216,0.000006234638,0.000001643896,0.000004369064,0.0001571127,0.00000306933,0.00004616379],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005752823,"threshold_uncertainty_score":0.01143867,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01865054382435799,"score_gpt":0.2371185811814572,"score_spread":0.2184680373570992,"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."}}