{"id":"W2110483583","doi":"10.1287/opre.2015.1349","title":"Technical Note—Trading Off Quick versus Slow Actions in Optimal Search","year":2015,"lang":"en","type":"article","venue":"Operations Research","topic":"Optimization and Search Problems","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Iterative deepening depth-first search; Set (abstract data type); Search algorithm; Order (exchange); Computer science; Beam stack search; Search engine; Search problem; Search cost; Linear search; Best-first search; Beam search; Algorithm; Information retrieval; Economics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004012538,0.001597012,0.002129098,0.00092473,0.001141013,0.002809981,0.00229734,0.002329195,0.00782445],"category_scores_gemma":[0.02231405,0.001056493,0.001568733,0.001125734,0.003486175,0.005189856,0.004148136,0.003519642,0.001164801],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001505065,"about_ca_system_score_gemma":0.002951128,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004493981,"about_ca_topic_score_gemma":0.002817553,"domain_scores_codex":[0.9968606,0.001144377,0.0001868873,0.000677172,0.0005718156,0.0005590686],"domain_scores_gemma":[0.9890803,0.00810623,0.0008136265,0.001006014,0.0004872249,0.0005066851],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003481194,0.0001537271,0.001907157,0.0003239464,0.0001101368,0.0002811069,0.0002329977,0.6882923,0.003700565,0.2659713,0.005659178,0.0330195],"study_design_scores_gemma":[0.00007364025,0.0001547446,0.0002424227,0.00007071224,0.0000364763,0.00009790616,0.00005089633,0.8039132,0.001104296,0.1916055,0.002615621,0.00003457907],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02404339,0.001201843,0.9549042,0.00145254,0.000153506,0.0001429984,0.0001805519,0.0003961246,0.01752489],"genre_scores_gemma":[0.6763455,0.002257982,0.3072267,0.001181147,0.0003983428,0.0005503772,0.0002684724,0.0004493813,0.01132209],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00782445,"threshold_uncertainty_score":0.02617538,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2697715929038695,"score_gpt":0.4593099383107204,"score_spread":0.1895383454068509,"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."}}