{"id":"W6948663810","doi":"10.5281/zenodo.11333709","title":"Sylvilagus (Sylvilagus) nuttallii","year":2005,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Data Management and Algorithms","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Subspecies; IUCN Red List; Allopatric speciation; Fauna; Endangered species","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":[0.00009714848,0.0004403902,0.0001585213,0.0008109543,0.0005137493,0.000188124,0.000339321,0.0001088224,0.004285513],"category_scores_gemma":[0.0001842652,0.0001152779,0.0001106707,0.0004156166,0.0001907657,0.0003920092,0.0004389543,0.0001736895,0.002140742],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003952823,"about_ca_system_score_gemma":0.000158767,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01336941,"about_ca_topic_score_gemma":0.05446751,"domain_scores_codex":[0.9999281,0.000005984093,0.000006719626,0.00002071341,0.00002924027,0.000009287837],"domain_scores_gemma":[0.9999095,0.000009207673,0.00004165794,0.000007714841,0.00002222774,0.000009785229],"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":[0.0003628034,0.0001849724,0.2406278,0.0006352168,0.0001131771,0.001325103,0.002542351,0.0006159822,0.09890439,0.006538341,0.04213584,0.6060141],"study_design_scores_gemma":[0.00002980845,0.0001670956,0.7490944,0.0001235835,0.0000596873,0.002188292,0.0004707292,0.0006447738,0.004284129,0.0007279166,0.2421916,0.00001806443],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7385577,0.0113038,0.005925431,0.0004980124,0.0004365709,0.0004033359,0.007695818,0.0005483468,0.234631],"genre_scores_gemma":[0.9501072,0.003143286,0.008541384,0.0003242767,0.00009246064,0.0001073702,0.005251198,0.00004249478,0.03239033],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01336941,"threshold_uncertainty_score":0.02658319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0278752146538934,"score_gpt":0.2338647150426426,"score_spread":0.2059895003887492,"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."}}