{"id":"W7080223520","doi":"10.5281/zenodo.16787074","title":"pEX Codebase: Anthropocene Imperilment of Ancient Diversity and Evolutionary Potential in Terrestrial Vertebrates","year":2025,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Geochemistry and Geologic Mapping","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Science Foundation","keywords":"Codebase; Phylogenetic tree; Directory; Selection (genetic algorithm); Heuristics; Feature (linguistics); Sample (material); Phylogenetics; Genetic programming","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":[0.00124694,0.001561722,0.001114227,0.004747028,0.0009008998,0.003562761,0.002343349,0.001101025,0.1684271],"category_scores_gemma":[0.01050278,0.000909389,0.001039955,0.00467251,0.0004261998,0.003165456,0.003187794,0.001613908,0.0942953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009564251,"about_ca_system_score_gemma":0.00177844,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008689193,"about_ca_topic_score_gemma":0.008405487,"domain_scores_codex":[0.9992121,0.00008097856,0.00008245988,0.0002576705,0.0003149284,0.00005176245],"domain_scores_gemma":[0.9975783,0.0009421248,0.0001400086,0.0005380212,0.0006627269,0.0001388078],"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":[0.00008343044,0.00001896617,0.00322164,0.0008432149,0.00008105086,0.00005822751,0.0001559292,0.001616091,0.0007542882,0.003216521,0.9541534,0.03579723],"study_design_scores_gemma":[0.00006912243,0.00002679164,0.01077603,0.0004407364,0.00007300575,0.0002078798,0.0001153282,0.003306317,0.001065796,0.00918644,0.9746832,0.00004923421],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.002896847,0.0007876569,0.01535511,0.0005112893,0.0005186534,0.00009146391,0.9467189,0.01991463,0.0132055],"genre_scores_gemma":[0.006907284,0.0008682501,0.01543985,0.0002157495,0.0001052722,0.0004283715,0.9539415,0.01374511,0.008348557],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.1684271,"threshold_uncertainty_score":0.5634449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01768345608825631,"score_gpt":0.2185551833792385,"score_spread":0.2008717272909822,"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."}}