{"id":"W6950111962","doi":"10.5281/zenodo.3810786","title":"Peropteryx kappleri Peters 1867","year":2019,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Bat Biology and Ecology Studies","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subspecies; Deciduous; Evergreen; Woodland; Subgenus","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005217041,0.0005711243,0.0002535293,0.001323701,0.000868388,0.0004002683,0.0003059758,0.0005322428,0.01902343],"category_scores_gemma":[0.0003191826,0.0002356606,0.0001131711,0.000598739,0.0004142397,0.001175978,0.0006033605,0.0004786859,0.007880762],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005053937,"about_ca_system_score_gemma":0.0002027133,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006531314,"about_ca_topic_score_gemma":0.008537709,"domain_scores_codex":[0.9998833,0.000006413539,0.000009555698,0.0000388102,0.00004465672,0.00001724738],"domain_scores_gemma":[0.9999135,0.00001322426,0.00003972369,0.000006693879,0.00001994885,0.000006973463],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002215765,0.00007732668,0.01821052,0.001079482,0.00004708951,0.001864871,0.0009752628,0.0005695728,0.01557526,0.006044121,0.05367761,0.9016573],"study_design_scores_gemma":[0.00004655715,0.0002313553,0.2165238,0.0007458918,0.00008258148,0.0129729,0.001174292,0.0005653997,0.004545403,0.002655657,0.7604217,0.0000345987],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.215133,0.04084743,0.006673316,0.001555305,0.001777833,0.0006626036,0.008841825,0.001044524,0.7234642],"genre_scores_gemma":[0.9168597,0.0138125,0.004734991,0.0005783832,0.0004163273,0.0001417579,0.00395372,0.00003949043,0.05946328],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01902343,"threshold_uncertainty_score":0.0636397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02856798991111454,"score_gpt":0.205696252462774,"score_spread":0.1771282625516594,"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."}}