{"id":"W4376644380","doi":"10.3390/logistics7020029","title":"Multiple Linear Regression Analysis of Canada’s Freight Transportation Framework","year":2023,"lang":"en","type":"article","venue":"Logistics","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Cape Breton University","funders":"","keywords":"Truck; Revenue; Transport engineering; Product (mathematics); Business; Regression analysis; Computer science; Engineering; Finance","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00007926309,0.0001037773,0.0002350863,0.0001372347,0.00003911286,0.000005305105,0.0000911279,0.0001022032,0.000163491],"category_scores_gemma":[0.0002290247,0.00009331178,0.00005931683,0.0007395914,0.00003077508,0.00001431103,0.000005626431,0.0001280023,0.000003277732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003421974,"about_ca_system_score_gemma":0.00005391516,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.02410395,"about_ca_topic_score_gemma":0.2003869,"domain_scores_codex":[0.9992189,0.000007997692,0.00027646,0.0001069815,0.0002001216,0.0001895838],"domain_scores_gemma":[0.9993961,0.0002217272,0.00004715299,0.0002131666,0.00005816421,0.00006363443],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004872006,0.00001058107,0.02088153,0.00009297304,0.0002344734,0.00007850121,0.0001229588,0.9648968,0.00007732691,0.003801749,0.009003586,0.0007946599],"study_design_scores_gemma":[0.00008216072,0.00001085381,0.1053274,0.00003109088,0.0004220734,2.028083e-7,0.00006481959,0.8810525,0.0005626513,0.0008620344,0.01140456,0.0001796208],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05750914,0.0002317774,0.9310927,0.0001527771,0.001383438,0.0001878863,0.001733689,0.00062052,0.007088018],"genre_scores_gemma":[0.9947079,0.0001015492,0.004223287,0.00002464712,0.0000612993,0.000003193191,0.0005814759,0.00001728431,0.0002793498],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9371988,"threshold_uncertainty_score":0.9823946,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01940441425275219,"score_gpt":0.2319168366237963,"score_spread":0.2125124223710441,"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."}}