{"id":"W2275602845","doi":"10.5539/mas.v10n4p47","title":"Product’s Selection for the Moroccan Technical Textile Industry by Using Custom’s Imports Data and Analytic Models","year":2016,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Global Trade and Competitiveness","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Analytic hierarchy process; Product (mathematics); Selection (genetic algorithm); Textile; Attractiveness; Investment (military); Value (mathematics); Manufacturing engineering; Textile industry; Business; Computer science; Industrial organization; Marketing; Operations research; Mathematics; Engineering; Statistics; Geography; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001436087,0.0006896284,0.0003543131,0.004933042,0.0008724324,0.001853715,0.0007078609,0.0003709002,0.007055222],"category_scores_gemma":[0.003743903,0.0002631826,0.001357919,0.003249407,0.0003638919,0.0008642552,0.0007944033,0.0003995443,0.0009916674],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003359438,"about_ca_system_score_gemma":0.002102451,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.04956327,"about_ca_topic_score_gemma":0.03964194,"domain_scores_codex":[0.9991724,0.0003004997,0.00005394439,0.0001402352,0.000219879,0.0001130437],"domain_scores_gemma":[0.9978734,0.001198071,0.0002582672,0.0001156419,0.0004789179,0.00007572995],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005499274,0.0006385955,0.5947049,0.0005540492,0.0003337063,0.00157959,0.004251992,0.1530978,0.003061915,0.02736664,0.009456245,0.2044046],"study_design_scores_gemma":[0.00006090797,0.0005458972,0.2412645,0.0002439811,0.0002662601,0.0005131498,0.008083013,0.7144653,0.002366254,0.006851978,0.02524122,0.0000975138],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9020407,0.0002810455,0.06344539,0.0006529751,0.00003219639,0.0007146618,0.00397169,0.000264363,0.02859701],"genre_scores_gemma":[0.9579461,0.0001560964,0.03423219,0.00002120885,0.000006944791,0.0002546964,0.003064049,0.00002133967,0.004297453],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04956327,"threshold_uncertainty_score":0.0985496,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05611084403253251,"score_gpt":0.2679366451817999,"score_spread":0.2118258011492674,"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."}}