{"id":"W3083464838","doi":"10.3390/jmse8090689","title":"Capturing Expert Knowledge to Inform Decision Support Technology for Marine Operations","year":2020,"lang":"en","type":"article","venue":"Journal of Marine Science and Engineering","topic":"Human-Automation Interaction and Safety","field":"Psychology","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Decision support system; Subject-matter expert; Knowledge base; Computer science; Expert system; Domain knowledge; Bridge (graph theory); Competence (human resources); Context (archaeology); Knowledge management; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.008934614,0.0005512047,0.000401844,0.004342755,0.0009349403,0.004209905,0.001274887,0.001290963,0.004084649],"category_scores_gemma":[0.03561698,0.0004188716,0.0004696307,0.001936363,0.001583081,0.006073011,0.002228114,0.001126592,0.0008424645],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001849486,"about_ca_system_score_gemma":0.002642969,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002808031,"about_ca_topic_score_gemma":0.004085558,"domain_scores_codex":[0.9933916,0.004216309,0.0004934364,0.0005340751,0.001125892,0.000238662],"domain_scores_gemma":[0.9690623,0.02444076,0.001336954,0.002506722,0.002257018,0.00039622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"qualitative","study_design_scores_codex":[0.0002049248,0.001653216,0.03599704,0.001844192,0.0001663195,0.0009737815,0.06598215,0.01524473,0.01444195,0.06053431,0.009770065,0.7931873],"study_design_scores_gemma":[0.0002486139,0.001265357,0.07203874,0.004643594,0.0003622492,0.001718949,0.1316298,0.1247378,0.02877947,0.4334006,0.2007727,0.0004020765],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3376304,0.001618464,0.5676883,0.00605666,0.0001543646,0.001448038,0.001015727,0.0007906289,0.08359751],"genre_scores_gemma":[0.6673471,0.001481664,0.325773,0.0007160096,0.00003929226,0.0004868464,0.0008426945,0.00005322472,0.003260226],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008934614,"threshold_uncertainty_score":0.04725134,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02733581719440557,"score_gpt":0.3497767618432259,"score_spread":0.3224409446488203,"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."}}