{"id":"W7097063504","doi":"","title":"Reverse Engineering: A Cognitive Approach, a Case Study and a Tool. Ph.d. computer science","year":2002,"lang":"en","type":"article","venue":"","topic":"Cognitive Science and Education Research","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Presentation (obstetrics); Cognition; Quality (philosophy); Nice; Key (lock)","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":[],"consensus_categories":[],"category_scores_codex":[0.0082514,0.0006404351,0.0003526362,0.002133016,0.004432126,0.005971172,0.001447062,0.003070723,0.003765278],"category_scores_gemma":[0.01410343,0.0003694726,0.0003959892,0.002486059,0.005557718,0.005409398,0.003550361,0.002002961,0.0006965061],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003468084,"about_ca_system_score_gemma":0.00410745,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001621471,"about_ca_topic_score_gemma":0.004182898,"domain_scores_codex":[0.9936997,0.004647695,0.0002580286,0.0002381135,0.0008705053,0.000285981],"domain_scores_gemma":[0.9869076,0.01029013,0.0007705621,0.0003176632,0.0009095559,0.0008044145],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.000213192,0.003164184,0.009134259,0.002502077,0.00003080115,0.02408359,0.2667077,0.00291307,0.007201769,0.1697955,0.05509681,0.459157],"study_design_scores_gemma":[0.0000824408,0.0009730279,0.008546728,0.002447289,0.0000628278,0.01453688,0.3980993,0.006275247,0.007580016,0.06472839,0.4965191,0.0001488796],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5551043,0.01283965,0.1736358,0.05475166,0.001371157,0.00342118,0.0002715489,0.0005103599,0.1980944],"genre_scores_gemma":[0.8185672,0.01055323,0.1228708,0.003365092,0.0001727934,0.001148866,0.0001545547,0.0001436671,0.04302373],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0082514,"threshold_uncertainty_score":0.04363811,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1264722910183054,"score_gpt":0.3406240148144193,"score_spread":0.214151723796114,"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."}}