{"id":"W2543825592","doi":"10.1080/00207543.2016.1251625","title":"Order picking problems under weight, fragility and category constraints","year":2016,"lang":"en","type":"article","venue":"International Journal of Production Research","topic":"Advanced Manufacturing and Logistics Optimization","field":"Engineering","cited_by":76,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Heuristics; Computer science; Heuristic; Mathematical optimization; Point (geometry); Order picking; Metaheuristic; Order (exchange); Operations research; Warehouse; Algorithm; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007702663,0.00006315014,0.00007785128,0.0002515264,0.00005096487,0.00003886223,0.000137904,0.00004046819,0.0001041489],"category_scores_gemma":[0.0004780629,0.00004414001,0.00001807902,0.00008511753,0.0002072402,0.0002810588,0.00003256969,0.0002402059,0.000007229898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001523403,"about_ca_system_score_gemma":0.00004380459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000431265,"about_ca_topic_score_gemma":0.000003538396,"domain_scores_codex":[0.9989988,0.00004972825,0.0002362018,0.0001134642,0.0004646017,0.0001372163],"domain_scores_gemma":[0.9985574,0.0001010985,0.00005679667,0.000079251,0.001149533,0.0000558553],"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":[0.0001383045,0.0001591718,0.004670032,0.0001050897,0.0004461493,0.00004659528,0.0006455606,0.6939718,0.04966274,0.0126202,0.004806877,0.2327275],"study_design_scores_gemma":[0.007578853,0.0007516659,0.05938105,0.001869031,0.00008054997,0.00319268,0.001545632,0.01230995,0.381966,0.4287254,0.1009871,0.001612149],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1536371,0.0004432068,0.8357297,0.005621568,0.002872289,0.0001570292,0.000005809962,0.00006612508,0.001467208],"genre_scores_gemma":[0.9949548,0.000761269,0.003413115,0.00000861834,0.0005205097,0.000002756962,0.000001074077,0.00001131658,0.0003264995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8413178,"threshold_uncertainty_score":0.1799977,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05802479152834462,"score_gpt":0.3378199354061194,"score_spread":0.2797951438777748,"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."}}