{"id":"W1635754461","doi":"","title":"Reverse-engineering graphical innovation: an introduction to graphical regimes","year":2013,"lang":"en","type":"article","venue":"DOAJ (DOAJ: Directory of Open Access Journals)","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal","funders":"","keywords":"Reverse engineering; Graphical model; Computer science; Software engineering; Data science; Programming language; Artificial intelligence","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":[],"consensus_categories":[],"category_scores_codex":[0.001663436,0.0009406897,0.0006841029,0.002456845,0.001182621,0.004263167,0.00161073,0.002344558,0.01418124],"category_scores_gemma":[0.005019578,0.0005257745,0.001614604,0.002919708,0.006894263,0.005384907,0.002210867,0.004254674,0.004358623],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002106795,"about_ca_system_score_gemma":0.0007546872,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001208383,"about_ca_topic_score_gemma":0.0009756395,"domain_scores_codex":[0.9982072,0.0008422898,0.0001310596,0.0002597947,0.0004298719,0.0001298032],"domain_scores_gemma":[0.9966355,0.002467594,0.0001910071,0.0004073982,0.0002257157,0.00007270347],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000005630235,0.00001815576,0.0001175116,0.000104564,0.000004044719,0.00005304693,0.0001851576,0.001418322,0.0001863831,0.9705182,0.005087935,0.02230101],"study_design_scores_gemma":[0.000004265765,0.0000293114,0.000207813,0.0002196865,0.000006845012,0.0003173106,0.000113624,0.005435045,0.0004532925,0.7058234,0.2873623,0.00002722315],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004585473,0.07245163,0.606772,0.009809717,0.002563569,0.0001351343,0.0002783378,0.0005293709,0.3028747],"genre_scores_gemma":[0.3204031,0.1446238,0.3793523,0.007384116,0.01060232,0.001029284,0.0006170391,0.001501043,0.134487],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01418124,"threshold_uncertainty_score":0.04744101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08310000140181523,"score_gpt":0.4259732559997359,"score_spread":0.3428732545979207,"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."}}