{"id":"W2271539076","doi":"10.1080/13675567.2015.1059412","title":"Developing an instrument to assess seaport effectiveness in service delivery","year":2015,"lang":"en","type":"article","venue":"International Journal of Logistics Research and Applications","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Port (circuit theory); Construct (python library); Container (type theory); Software deployment; Service (business); Measure (data warehouse); Variance (accounting); Computer science; Population; Service delivery framework; Formative assessment; Process management; Engineering; Operations management; Business; Marketing; Software engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01372117,0.0004310415,0.000360495,0.002813183,0.0005518071,0.001833929,0.0008801625,0.0005567404,0.002661243],"category_scores_gemma":[0.03176818,0.000230645,0.0004508572,0.002693521,0.0005600778,0.002136931,0.001622972,0.0007867197,0.0006717046],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001411874,"about_ca_system_score_gemma":0.003138186,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002469113,"about_ca_topic_score_gemma":0.003085956,"domain_scores_codex":[0.989488,0.00508548,0.001310275,0.0003681235,0.003248166,0.0004999752],"domain_scores_gemma":[0.9690254,0.01456797,0.003936615,0.001339028,0.0102323,0.0008987105],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002769841,0.001549201,0.6500623,0.0004328911,0.000117498,0.0001401706,0.006455902,0.003274587,0.004332665,0.005442528,0.006513707,0.3214015],"study_design_scores_gemma":[0.0001023105,0.004144392,0.9142458,0.0004137463,0.000107193,0.000323592,0.01611325,0.02366084,0.01055232,0.003096574,0.02711064,0.0001294338],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.9179631,0.0001285129,0.05451403,0.0003896921,0.00007761824,0.003241889,0.001352282,0.0003855484,0.02194729],"genre_scores_gemma":[0.8625985,0.0001923235,0.1288402,0.0001867197,0.00003060851,0.004260139,0.002108064,0.00004672174,0.001736693],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.01372117,"threshold_uncertainty_score":0.07256532,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.3112641554352228,"score_gpt":0.4379282855512153,"score_spread":0.1266641301159924,"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."}}