{"id":"W4252524180","doi":"10.1080/07408170108936887","title":"The plant location and technology acquisition problem","year":2001,"lang":"en","type":"article","venue":"IIE Transactions","topic":"Facility Location and Emergency Management","field":"Business, Management and Accounting","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Science Council","keywords":"Set (abstract data type); Mathematical optimization; Computer science; Product (mathematics); Selection (genetic algorithm); Piecewise linear function; Piecewise; Industrial engineering; Operations research; Engineering; Mathematics; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0013243,0.001257955,0.001573941,0.001111753,0.0009950157,0.0022194,0.001908584,0.003430972,0.01633401],"category_scores_gemma":[0.003959736,0.001024145,0.001086857,0.001914513,0.001182795,0.003270487,0.002084416,0.00237833,0.001214991],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001995788,"about_ca_system_score_gemma":0.002927859,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006761116,"about_ca_topic_score_gemma":0.00482375,"domain_scores_codex":[0.9985843,0.0005521222,0.00004253066,0.0003464276,0.0002570765,0.0002175632],"domain_scores_gemma":[0.9984792,0.001075883,0.0001632312,0.00006980219,0.0001037799,0.0001082002],"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":[0.0001440942,0.000127507,0.0009554016,0.0002904259,0.00006730502,0.0004992966,0.0001293274,0.792775,0.001170673,0.1578108,0.006012939,0.04001724],"study_design_scores_gemma":[0.00009325022,0.0001070543,0.0006125903,0.00003986344,0.00004450677,0.000314442,0.000182546,0.8762823,0.001075603,0.1079067,0.01329541,0.00004571264],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03170984,0.0004911806,0.9466137,0.001990764,0.0001163919,0.0002146262,0.0008836853,0.0002076047,0.01777228],"genre_scores_gemma":[0.611899,0.001444797,0.3491275,0.0003696504,0.0002765234,0.0007105276,0.001527106,0.0001837174,0.03446126],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01633401,"threshold_uncertainty_score":0.05464274,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01622155327207972,"score_gpt":0.2074896994078609,"score_spread":0.1912681461357812,"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."}}