{"id":"W6961147526","doi":"10.14473/csda/qjwlgn/60cspl","title":"D05_CHPS301.pdf","year":2024,"lang":"cs","type":"dataset","venue":"Czech Social Science Data Archive","topic":"DNA and Biological Computing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Standards Association","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","routes":{"ca_aff":true,"ca_fund":false,"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":["metaepi_narrow","sts","open_science","insufficient_payload"],"consensus_categories":["sts","open_science"],"category_scores_codex":[0.001740133,0.0006150149,0.0005199979,0.0001731987,0.001381153,0.0006639304,0.007395376,0.000575872,0.0002900558],"category_scores_gemma":[0.0009740085,0.0005079011,0.0002195387,0.000875601,0.003655148,0.00003848909,0.01434642,0.001013579,0.007631513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007469931,"about_ca_system_score_gemma":0.001229757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001038761,"about_ca_topic_score_gemma":0.00009926251,"domain_scores_codex":[0.9943116,0.0002167261,0.0005630604,0.002824139,0.0007808278,0.001303703],"domain_scores_gemma":[0.9972165,0.00009502957,0.0002746357,0.001909258,0.0001239122,0.0003806677],"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":[0.00003578054,0.000105001,0.00001844314,0.0001139158,0.00007089668,0.00005318086,0.00008314631,3.326147e-7,0.05849556,0.0002084537,0.9284594,0.01235588],"study_design_scores_gemma":[0.0001624591,0.00032651,0.0001496898,0.0000936444,0.0001298999,0.00002217955,0.0002708994,0.000195231,0.001290101,0.0008912523,0.9957498,0.0007183345],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.002527468,0.0006154972,0.000146888,0.0003991482,0.002031013,0.00040558,0.9865904,0.00003490186,0.007249127],"genre_scores_gemma":[0.008142141,0.0008276884,0.0004706896,0.001144648,0.004416429,0.00001234673,0.9844219,0.00002633827,0.0005378167],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.06729039,"threshold_uncertainty_score":0.9999189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03605023138704542,"score_gpt":0.3443455764376257,"score_spread":0.3082953450505803,"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."}}