{"id":"W26708431","doi":"10.1007/978-1-4757-9859-3_7","title":"Karush-Kuhn-Tucker Theory","year":2000,"lang":"en","type":"book-chapter","venue":"","topic":"Cognitive Science and Mapping","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo; Simon Fraser University","funders":"","keywords":"Karush–Kuhn–Tucker conditions; Inequality; Mathematics; Mathematical optimization; Mathematical analysis","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":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.00038861,0.0002830048,0.0002420336,0.0002108064,0.0001403106,0.0001994828,0.001244978,0.0001731486,0.00497356],"category_scores_gemma":[0.00001275334,0.0002355312,0.0001740552,0.00006891158,0.0001420453,0.0004152949,0.000374257,0.000278557,0.005497528],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000335495,"about_ca_system_score_gemma":0.0001479829,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004475351,"about_ca_topic_score_gemma":0.000007864178,"domain_scores_codex":[0.9983001,0.00001889995,0.0002249684,0.0006957069,0.0004280448,0.0003322703],"domain_scores_gemma":[0.9988862,0.000121633,0.00007956707,0.0006972678,0.0000892966,0.0001260442],"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":[0.000001186004,0.000003041544,2.206408e-7,0.000002019572,0.00000897451,0.00002240582,0.00006932631,2.686689e-7,0.000007450456,0.696573,0.002432787,0.3008793],"study_design_scores_gemma":[0.00005314308,0.00002366548,0.000008778636,0.00004704511,0.000006138421,0.00001553926,0.000002884474,0.00009612263,0.00003969159,0.4865773,0.5128772,0.0002524882],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.000001148577,0.0002232448,0.1456876,0.0003167182,0.0003227326,0.0001345568,0.000003183605,0.0002350746,0.8530757],"genre_scores_gemma":[0.0007834797,0.0002144624,0.004435468,0.003401568,0.0001935495,0.000005105751,0.000004096263,0.00001846103,0.9909438],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5104445,"threshold_uncertainty_score":0.995936,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01929157501743594,"score_gpt":0.2203471163706743,"score_spread":0.2010555413532384,"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."}}