{"id":"W2134234780","doi":"10.1186/1751-0473-7-2","title":"Changing computational research. The challenges ahead","year":2012,"lang":"en","type":"article","venue":"Source Code for Biology and Medicine","topic":"Scientific Computing and Data Management","field":"Decision Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université TÉLUQ; Université du Québec à Montréal","funders":"","keywords":"Computer science; Data science; Set (abstract data type); Replication (statistics); Code (set theory); Test (biology); Open research; Open science; World Wide Web; Programming language","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.08831459,0.00166928,0.002287993,0.00369196,0.01189915,0.023526,0.00755795,0.03802569,0.02943313],"category_scores_gemma":[0.2078679,0.0009407403,0.002908506,0.004784895,0.03732932,0.07287118,0.01511954,0.06493063,0.0166942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01079925,"about_ca_system_score_gemma":0.02260763,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004325682,"about_ca_topic_score_gemma":0.007183072,"domain_scores_codex":[0.9416868,0.02571149,0.004292316,0.005596794,0.01899689,0.003715749],"domain_scores_gemma":[0.6696067,0.2143968,0.007725812,0.03161543,0.05360077,0.02305459],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0000866312,0.00009819766,0.0002396513,0.0008463687,0.00003197216,0.0001052088,0.001340665,0.0002052187,0.000181705,0.254411,0.6846281,0.05782535],"study_design_scores_gemma":[0.0000316624,0.00003839919,0.0003474983,0.001200365,0.000009352598,0.000171009,0.002797446,0.0001954199,0.00007843279,0.1881251,0.8069519,0.00005336602],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001392877,0.01565172,0.001558176,0.9585901,0.02143858,0.00001095694,0.00004751115,0.00009712539,0.002466435],"genre_scores_gemma":[0.01352443,0.03572934,0.01787826,0.862494,0.06129796,0.0001563952,0.0002446973,0.0006255188,0.008049445],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9116854,"threshold_uncertainty_score":0.4670578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.4472434062920214,"score_gpt":0.5171791647165314,"score_spread":0.06993575842450994,"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."}}