{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005391432,0.0001147728,0.0001026263,0.0002978752,0.0004242279,0.0002828595,0.0001950577,0.00001697962,0.0002896857],"category_scores_gemma":[0.001010533,0.00009410462,0.00002068414,0.001410646,0.0005646563,0.0005525497,0.0002176859,0.0001531964,0.0001135219],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002644275,"about_ca_system_score_gemma":0.00005570726,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007205561,"about_ca_topic_score_gemma":0.000003262014,"domain_scores_codex":[0.9982568,0.00005789465,0.000127339,0.0006631104,0.0004993522,0.0003955272],"domain_scores_gemma":[0.9991654,0.0003005085,0.00002298969,0.0001653132,0.000149153,0.0001966594],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001029079,0.01606794,0.02412403,0.0001812774,0.00004504362,0.01550319,0.1543165,0.0001522454,0.1293869,0.003633547,0.007316984,0.6491694],"study_design_scores_gemma":[0.003136121,0.00158259,0.007899694,0.00005040023,0.00003823024,0.01387536,0.04977126,0.8985246,0.02309625,0.00005185368,0.0009065425,0.001067101],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9917183,0.000006970093,0.003340464,0.0001544247,0.000103609,0.0006291468,0.000002997459,0.00006174715,0.00398237],"genre_scores_gemma":[0.9976187,0.000006901136,0.0007886634,0.0006077735,0.00005018595,0.00005539605,1.04121e-7,0.000005940167,0.0008662909],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8983724,"threshold_uncertainty_score":0.3837475,"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."}}