{"id":"W4362579980","doi":"10.3390/technologies11020051","title":"HAIS: Highways Automated-Inspection System","year":2023,"lang":"en","type":"article","venue":"Technologies","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University","funders":"","keywords":"Computer science; Process (computing); Visualization; Interface (matter); Overlay; Software; Transport engineering; Systems engineering; Engineering; 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":[{"model":"gemma","categories":[],"domain":null,"study_design":"simulation_or_modeling","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"medium","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"not_applicable","genre":"software","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004689977,0.0009494415,0.000731685,0.001249944,0.0003437577,0.0008595961,0.001572914,0.0005258672,0.02303475],"category_scores_gemma":[0.0008895094,0.0002790263,0.0002558847,0.0005718074,0.0002287534,0.000809098,0.0009309559,0.0005414759,0.01145447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006723265,"about_ca_system_score_gemma":0.000692949,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00414596,"about_ca_topic_score_gemma":0.002336926,"domain_scores_codex":[0.9995719,0.00004539824,0.00003212022,0.0001330085,0.000145326,0.00007217284],"domain_scores_gemma":[0.9994951,0.00006307969,0.00006987281,0.0001246204,0.0001892585,0.00005806055],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002248874,0.0005621032,0.02006483,0.0006139507,0.0002170124,0.0005510713,0.0002759193,0.02192847,0.02507812,0.006608329,0.6648899,0.2569614],"study_design_scores_gemma":[0.0004514805,0.0005726982,0.01891315,0.00008871334,0.0001251141,0.0005750919,0.000122904,0.6808619,0.0525209,0.005322575,0.2402582,0.000187269],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"software","genre_gemma":"empirical","genre_scores_codex":[0.03693888,0.0004991617,0.1025376,0.0003522584,0.0002495949,0.0006129813,0.02394166,0.7964132,0.03845474],"genre_scores_gemma":[0.8063704,0.0004200029,0.06659514,0.0008728963,0.0002165182,0.000777007,0.07764681,0.005093659,0.04200766],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.02303475,"threshold_uncertainty_score":0.07705891,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00787166430729769,"score_gpt":0.2001777339930808,"score_spread":0.1923060696857831,"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."}}