{"id":"W2754752206","doi":"10.1016/j.tcs.2017.08.023","title":"A general framework for searching on a line","year":2017,"lang":"en","type":"article","venue":"Theoretical Computer Science","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa; Carleton University","funders":"","keywords":"Competitive analysis; Constant (computer programming); Search cost; Mathematics; Mathematical optimization; Line (geometry); Search problem; Upper and lower bounds; Fixed cost; Computer science","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":["sts","scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.001825979,0.0001305172,0.0001480032,0.0001324655,0.001859716,0.002146072,0.004366049,0.00004876455,0.00001955521],"category_scores_gemma":[0.0006770394,0.0001021619,0.0000670691,0.0002332081,0.00181545,0.0006761811,0.001273855,0.000243561,0.00005208407],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003476412,"about_ca_system_score_gemma":0.0001285095,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001851508,"about_ca_topic_score_gemma":1.941244e-7,"domain_scores_codex":[0.9979151,0.00006174561,0.0001692351,0.0006381779,0.0006157514,0.000599939],"domain_scores_gemma":[0.9975824,0.0003708826,0.00007557801,0.00145219,0.0002075865,0.0003113658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008735407,0.00003888346,0.00001048983,0.000004257114,0.000001824788,0.000002943595,0.0002212658,0.002183396,0.00005986366,0.9406462,0.00003753652,0.05678455],"study_design_scores_gemma":[0.0001370616,0.0002579852,0.000113717,0.00002519268,5.674283e-7,0.00000286447,5.220821e-7,0.5895979,0.0008049106,0.408841,0.0001297575,0.00008853066],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002753181,0.000002939501,0.9848952,0.008376999,0.0005636326,0.0002827908,0.000001719303,0.0001326218,0.002990909],"genre_scores_gemma":[0.464942,0.000002064801,0.533928,0.0009093055,0.0001739083,0.0000111029,2.665562e-7,0.000004712139,0.00002863521],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5874144,"threshold_uncertainty_score":0.9994397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04851479088591047,"score_gpt":0.3635690444791842,"score_spread":0.3150542535932737,"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."}}