{"id":"W609176152","doi":"","title":"STUDY LOOKING AT RUNWAY INCURSIONS IDENTIFIES CONTRIBUTING FACTORS AND RECOMMENDS SOLUTIONS","year":2002,"lang":"en","type":"article","venue":"ICAO bulletin","topic":"Maritime Ports and Logistics","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Runway; Subtitle; Transport engineering; Volume (thermodynamics); Engineering; Aeronautics; Computer science; Geography; Physics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0007132636,0.000395177,0.0002813047,0.002447165,0.001240634,0.001232049,0.0006915649,0.0004819682,0.009610197],"category_scores_gemma":[0.004771122,0.0001422581,0.00056305,0.003037181,0.0004555008,0.001444215,0.0006771584,0.0006274687,0.0008245317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001067364,"about_ca_system_score_gemma":0.002817961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01778234,"about_ca_topic_score_gemma":0.07008965,"domain_scores_codex":[0.9991329,0.0001696431,0.00007887105,0.00007840623,0.0002754611,0.0002646765],"domain_scores_gemma":[0.993838,0.001414497,0.001981615,0.000194148,0.001859265,0.0007125092],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008155948,0.0003134516,0.9380317,0.0004689706,0.00007640119,0.001301474,0.00303873,0.000330234,0.001486133,0.0006653492,0.00158297,0.052623],"study_design_scores_gemma":[0.00000265564,0.0002520741,0.9698021,0.0001583145,0.00006902564,0.000841352,0.02285073,0.0003324055,0.0006911862,0.0003550908,0.004626124,0.00001881308],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9877479,0.0009203384,0.001687253,0.0009819907,0.00005022388,0.000130087,0.000748359,0.00005611226,0.007677694],"genre_scores_gemma":[0.9942508,0.0009606708,0.001358636,0.00009787802,0.00003246688,0.00004345225,0.0004749207,0.000009716045,0.002771428],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01778234,"threshold_uncertainty_score":0.03535765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03193541893294083,"score_gpt":0.2188381415716994,"score_spread":0.1869027226387586,"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."}}