{"id":"W6887880867","doi":"10.17632/csd32bm8zx.1","title":"Dataset for Drone-based Inspection of Road Pavement Structures for Cracks","year":2022,"lang":"en","type":"dataset","venue":"Data Archiving and Networked Services (DANS)","topic":"Infrastructure Maintenance and Monitoring","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Drone; Visual inspection; Aerial survey; Benchmarking; Aerial photography; Road surface","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":[0.0005994096,0.003069107,0.001541334,0.003421758,0.0008101202,0.001309771,0.002969061,0.002606412,0.009311195],"category_scores_gemma":[0.00203656,0.0004382375,0.001464484,0.003190928,0.0004853795,0.0009615838,0.001460462,0.001414591,0.01664886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001484346,"about_ca_system_score_gemma":0.001498061,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05033828,"about_ca_topic_score_gemma":0.1199972,"domain_scores_codex":[0.9988606,0.000109486,0.000113651,0.0003595364,0.0003620806,0.0001947425],"domain_scores_gemma":[0.9988289,0.0001802727,0.0000950038,0.0003308485,0.0004359602,0.0001289747],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002478924,0.000307591,0.007113007,0.001729691,0.0001522526,0.0002910209,0.00009362175,0.005389088,0.002040188,0.0005707041,0.9585456,0.02351941],"study_design_scores_gemma":[0.0003639438,0.0001987979,0.05456568,0.000757491,0.0001392714,0.0006821061,0.0005925692,0.02455427,0.006491215,0.001920645,0.9095309,0.0002031076],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.005201968,0.0003861722,0.0008492088,0.0001218277,0.00009379574,0.00008307497,0.988727,0.002838191,0.001698769],"genre_scores_gemma":[0.002964717,0.00006387686,0.001113413,0.0000267041,0.000006562584,0.00005952582,0.9952153,0.00005017809,0.0004997639],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05033828,"threshold_uncertainty_score":0.1000906,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0137157404732993,"score_gpt":0.2550634067562795,"score_spread":0.2413476662829802,"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."}}