{"id":"W7092198381","doi":"10.5281/zenodo.17368935","title":"Data Availability Part 2","year":2025,"lang":"","type":"dataset","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Research Data Management Practices","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fractal; Genetic algorithm; Code (set theory); Binary number; Genetic code; Work (physics); Genetic data","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.008981782,0.002170887,0.004724854,0.01131832,0.00398895,0.0113126,0.006448918,0.005661779,0.8479151],"category_scores_gemma":[0.08001523,0.002079135,0.00248592,0.01694416,0.002508087,0.0069413,0.007027493,0.004727375,0.5371039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003734244,"about_ca_system_score_gemma":0.01572878,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008558958,"about_ca_topic_score_gemma":0.008229429,"domain_scores_codex":[0.9880844,0.001695398,0.003035848,0.002194705,0.003952964,0.001036701],"domain_scores_gemma":[0.9378975,0.02284066,0.002989536,0.01481058,0.01878797,0.002673655],"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":[0.0002328093,0.00002830026,0.0002630972,0.004123109,0.00004165864,0.000106891,0.0001444519,0.0002551142,0.0002711748,0.004798522,0.9764575,0.01327732],"study_design_scores_gemma":[0.0002130452,0.00002439366,0.0007617458,0.002071531,0.00003127999,0.0001076194,0.0001661445,0.0001583097,0.0003160566,0.006961343,0.9891306,0.00005799745],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0001508292,0.0001953635,0.002048138,0.0008678294,0.001201182,0.0005037431,0.9755585,0.003292745,0.01618179],"genre_scores_gemma":[0.004818778,0.0009963524,0.0154995,0.003034782,0.0005139765,0.01085363,0.9122381,0.006599212,0.04544555],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1520849,"threshold_uncertainty_score":0.2169306,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1680240968226684,"score_gpt":0.3448807926454774,"score_spread":0.176856695822809,"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."}}