{"id":"W2981515357","doi":"10.1007/978-3-030-26676-9","title":"Fuzzy Transportation and Transshipment Problems","year":2019,"lang":"en","type":"book","venue":"Studies in fuzziness and soft computing","topic":"Transportation Planning and Optimization","field":"Social Sciences","cited_by":19,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia, Okanagan Campus; University of British Columbia","funders":"","keywords":"Transshipment (information security); Fuzzy transportation; Fuzzy logic; Transportation theory; Computer science; Operations research; Mathematical optimization; Fuzzy set operations; Engineering; Fuzzy set; 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":[0.0005736,0.001048662,0.000764221,0.001039035,0.0007988993,0.001795625,0.0008163941,0.001134758,0.008583618],"category_scores_gemma":[0.001319399,0.0002935359,0.0008464443,0.002545374,0.001223958,0.002414973,0.0005618859,0.001983078,0.0006124311],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001822877,"about_ca_system_score_gemma":0.0009442186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006232803,"about_ca_topic_score_gemma":0.004369853,"domain_scores_codex":[0.999813,0.0000526059,0.000009296178,0.00003391359,0.00007156995,0.00001964624],"domain_scores_gemma":[0.9997248,0.0001734593,0.00001690378,0.00001930079,0.00004730577,0.00001813224],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00003476391,0.00004136175,0.0001894966,0.000190797,0.00003188185,0.00007435869,0.0001457246,0.05424637,0.0003467354,0.8416966,0.02803855,0.07496329],"study_design_scores_gemma":[0.00001104903,0.00002312454,0.0004862372,0.0000794367,0.00001611557,0.000116412,0.0001398691,0.0779134,0.0001569305,0.8758714,0.04517116,0.00001494142],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.05156524,0.1081195,0.3818469,0.01201263,0.002560628,0.00008696487,0.000760273,0.0001583071,0.4428895],"genre_scores_gemma":[0.5192605,0.09567335,0.1110488,0.0009854042,0.003227342,0.0001987914,0.00102854,0.0001446116,0.2684326],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008583618,"threshold_uncertainty_score":0.02871501,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04746413163775181,"score_gpt":0.3204007413398831,"score_spread":0.2729366097021312,"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."}}