{"id":"W4293568975","doi":"10.1111/ecog.06287","title":"A protocol for reproducible functional diversity analyses","year":2022,"lang":"en","type":"article","venue":"Ecography","topic":"Species Distribution and Climate Change","field":"Environmental Science","cited_by":75,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Horizon 2020 Framework Programme; Mitacs; Consejo Nacional de Investigaciones Científicas y Técnicas; Akademie Věd České Republiky; European Commission","keywords":"Protocol (science); Computer science; Metadata; Comparability; Data science; Workflow; Ecology; Checklist; Trait; Transparency (behavior); Diversity (politics); Data mining; Biology; Database; World Wide Web; Mathematics; Medicine","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0001837798,0.0000538717,0.00005397158,0.00003837404,0.0008557528,0.00001166874,0.0001195519,0.00001007907,0.2403026],"category_scores_gemma":[0.00001151664,0.00005274616,0.0001265942,0.0004372771,0.00005359771,0.00006267025,0.000498681,0.00004585461,0.0001276943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001235328,"about_ca_system_score_gemma":0.000002824649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009459195,"about_ca_topic_score_gemma":0.00004320739,"domain_scores_codex":[0.9992973,0.00002044522,0.00007073994,0.0002665028,0.0002103024,0.0001347697],"domain_scores_gemma":[0.999728,0.00001270964,0.00004256757,0.000171623,0.000005903446,0.00003923989],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001471967,0.0002954869,0.3543688,0.000008430586,0.00002225723,0.000001241846,0.0001057749,0.0002407203,0.001218789,0.0004450297,0.6426404,0.0005058692],"study_design_scores_gemma":[0.000454801,0.00008838583,0.3123181,3.123106e-7,0.000007254963,0.000001619771,0.0004323282,0.0000252871,0.0003925825,0.0004359309,0.6857643,0.00007904587],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"protocol","genre_scores_codex":[0.4046712,0.0000161859,0.001520369,0.003416985,0.0008483491,0.2634421,0.001290679,0.0005373556,0.3242568],"genre_scores_gemma":[0.3107713,6.803232e-7,0.0002785986,0.001256096,0.0000890208,0.6836234,0.0002439567,0.00001497561,0.003721936],"genre_candidate":"protocol","genre_consensus":null,"teacher_disagreement_score":0.4201814,"threshold_uncertainty_score":0.7603919,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1897999159361005,"score_gpt":0.3461755552759557,"score_spread":0.1563756393398553,"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."}}