{"id":"W2246316383","doi":"","title":"Reverse Engineering of Software: Copyright and Interoperability","year":2003,"lang":"en","type":"article","venue":"Journal of Law Information & Science","topic":"Law, AI, and Intellectual Property","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Copying; Reverse engineering; Interoperability; Copyright infringement; Fair use; Software; Intellectual property; Legislation; Computer security; Computer science; Software engineering; Law; Law and economics; World Wide Web; Political science; Sociology; Programming language","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":[0.001536287,0.0000638717,0.0001299112,0.0001240756,0.0001073127,0.0001696542,0.0005485342,0.00001784878,0.0000201668],"category_scores_gemma":[0.0008713341,0.00004239524,0.00003672129,0.0003957642,0.0003555636,0.008575412,0.00008033423,0.0001114449,0.000007000511],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005694025,"about_ca_system_score_gemma":0.0001750764,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001100913,"about_ca_topic_score_gemma":7.218354e-7,"domain_scores_codex":[0.9988635,0.00002244638,0.0004925892,0.00006673393,0.0004198396,0.0001349595],"domain_scores_gemma":[0.9988068,0.0000613203,0.0002571032,0.0001803614,0.0005904204,0.0001040465],"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":[0.00005387306,0.0001580341,0.0016038,0.0002678873,0.0000338409,0.000006093409,0.0323481,0.002907945,0.01768157,0.9111454,0.003416985,0.03037647],"study_design_scores_gemma":[0.002201984,0.001714884,0.004187709,0.0004870301,0.00002535282,0.001538728,0.0005250996,0.180878,0.3691328,0.007327285,0.4311665,0.0008145603],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1240593,0.0000749866,0.8643413,0.0002326217,0.0008404559,0.00009668504,9.849647e-7,0.00002459639,0.01032908],"genre_scores_gemma":[0.9543376,0.00002633784,0.04529353,0.0003226359,0.000008339573,2.930534e-7,4.361805e-8,0.000001065402,0.00001013643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9038181,"threshold_uncertainty_score":0.6216967,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01204076656530982,"score_gpt":0.2130410778655558,"score_spread":0.201000311300246,"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."}}