{"id":"W2901297776","doi":"10.2172/1481626","title":"Toward a Compatible Reproducibility Taxonomy for Computational and Computing Sciences","year":2018,"lang":"en","type":"report","venue":"","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Institute of Standards and Technology; University of Pittsburgh; York University; Sandia National Laboratories; U.S. Department of Energy; National Science Foundation","keywords":"Computer science; Taxonomy (biology); Replication (statistics); Data science; Reproducibility; Management science; Mathematics; Engineering; Biology; Ecology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch","metaepi_narrow","scholarly_communication"],"consensus_categories":["metaresearch"],"category_scores_codex":[0.07367548,0.0003435153,0.0007936132,0.00072031,0.001060732,0.002164319,0.001745665,0.0001286483,0.0003048791],"category_scores_gemma":[0.02135271,0.0002494577,0.0002152672,0.001197161,0.001141571,0.0002549859,0.001907371,0.0001689403,0.0001196878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001317872,"about_ca_system_score_gemma":0.001281778,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003142517,"about_ca_topic_score_gemma":0.00006831274,"domain_scores_codex":[0.988475,0.0002149595,0.001679691,0.005174286,0.003945367,0.0005107133],"domain_scores_gemma":[0.9884108,0.004505513,0.001152002,0.002796038,0.002947537,0.0001881546],"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":[0.00001109476,0.00007133368,0.005902959,0.00009631636,0.00003944632,0.000001558377,0.0001480531,0.001215062,4.698743e-7,0.002137802,0.9006042,0.0897717],"study_design_scores_gemma":[0.0002957594,0.0001814289,0.005198957,0.00009932942,0.00003800011,0.00003342556,0.0007330265,0.1770605,0.000008338081,0.03543656,0.7804726,0.0004419979],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00989425,0.0004922463,0.6268378,0.001501334,0.008873773,0.002808086,0.0003878871,0.0002897194,0.3489149],"genre_scores_gemma":[0.5874341,0.00001753741,0.3830587,0.0005148194,0.002307366,0.00008047382,0.0003526919,0.00003877187,0.02619557],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5775398,"threshold_uncertainty_score":0.9999958,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6666905415006609,"score_gpt":0.4953811842910563,"score_spread":0.1713093572096046,"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."}}