{"id":"W2104435566","doi":"10.5267/j.msl.2012.10.009","title":"Improving efficiencies in logistics operations by converging tangible & intangible aspects","year":2012,"lang":"en","type":"article","venue":"Management Science Letters","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Process management; Business; Knowledge management; Operations management","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":[0.003237209,0.001224013,0.000490132,0.002622967,0.0009828756,0.009829949,0.001108985,0.001026483,0.004602882],"category_scores_gemma":[0.005861125,0.000383665,0.0006858335,0.00251027,0.004835154,0.009083875,0.006210879,0.001564926,0.000886888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001833679,"about_ca_system_score_gemma":0.003702914,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009388757,"about_ca_topic_score_gemma":0.002073367,"domain_scores_codex":[0.9971112,0.0008329661,0.0001938882,0.0002423808,0.001282176,0.0003373434],"domain_scores_gemma":[0.9966599,0.001382473,0.0007860469,0.000453783,0.0005216857,0.0001961861],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001667618,0.0003845638,0.00941714,0.001596438,0.0001235366,0.0005470588,0.002872797,0.05286467,0.01450253,0.5788504,0.0007394041,0.3379347],"study_design_scores_gemma":[0.0000516716,0.0009966512,0.02550802,0.001743411,0.0002761589,0.0007765259,0.01017865,0.03117928,0.02732139,0.8168446,0.08496002,0.0001635946],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2939561,0.005828791,0.4251322,0.004965886,0.0001365927,0.0002482633,0.0001292952,0.0002967234,0.2693062],"genre_scores_gemma":[0.90497,0.004419256,0.08358476,0.0001899354,0.00007635989,0.00009748118,0.00006835711,0.00005596784,0.006537893],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009829949,"threshold_uncertainty_score":0.01712018,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01135715290867225,"score_gpt":0.2164700327205213,"score_spread":0.205112879811849,"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."}}