{"id":"W3122982456","doi":"","title":"Optimal resource extraction contract with adverse selection","year":2006,"lang":"en","type":"article","venue":"HAL (Le Centre pour la Communication Scientifique Directe)","topic":"Mining Techniques and Economics","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Adverse selection; Selection (genetic algorithm); Extraction (chemistry); Resource (disambiguation); Computer science; Business; Actuarial science; Artificial intelligence; Chemistry; Chromatography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000984999,0.0001351937,0.0001236113,0.00008287324,0.0001458799,0.00008134005,0.0001762937,0.00009191644,0.0001152592],"category_scores_gemma":[0.00004449738,0.0001446356,0.00004770632,0.0001705808,0.00004733343,0.0001934116,0.00002840923,0.0001912064,0.00002385141],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001019042,"about_ca_system_score_gemma":0.00002209059,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004915803,"about_ca_topic_score_gemma":0.001026068,"domain_scores_codex":[0.9990148,0.0002586381,0.0002149094,0.0002094554,0.000096413,0.0002058143],"domain_scores_gemma":[0.9990634,0.0001978904,0.00008699033,0.0003832809,0.0002115759,0.0000568833],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0002660915,0.001767824,0.0407644,0.0003540097,0.0003680789,0.00004343391,0.009254351,0.3238311,0.1327367,0.2667033,0.05540964,0.1685011],"study_design_scores_gemma":[0.0009188929,0.00000175805,0.01606085,0.0003654689,0.00004261799,0.00009773453,0.0001196452,0.5691089,0.2370806,0.0003611331,0.1752232,0.0006191542],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6180812,0.00008727977,0.2879086,0.0004079969,0.0000371475,0.000146183,0.000006305634,0.0007626101,0.09256266],"genre_scores_gemma":[0.9258267,0.00003922255,0.07168569,0.00001571845,0.00002441106,0.00002237534,0.00006894719,0.00003505621,0.002281867],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3077455,"threshold_uncertainty_score":0.589807,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00598192277848844,"score_gpt":0.1871175000172706,"score_spread":0.1811355772387822,"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."}}