{"id":"W6926873099","doi":"10.25545/6dgf1v","title":"Camera-LiDAR Datasets","year":2024,"lang":"en","type":"dataset","venue":"UNB Dataverse","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Lidar; Mobile mapping; Data collection; Matching (statistics); Tree (set theory); Aerial survey; Laser scanning; Data acquisition","routes":{"ca_aff":true,"ca_fund":false,"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":[0.001400785,0.003318968,0.002069711,0.004038354,0.001474669,0.001944426,0.004839876,0.003325903,0.02672325],"category_scores_gemma":[0.003721914,0.0006056403,0.001495416,0.007130467,0.0007405081,0.002021708,0.002424428,0.00224454,0.06877069],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001499167,"about_ca_system_score_gemma":0.001940596,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02124823,"about_ca_topic_score_gemma":0.06209359,"domain_scores_codex":[0.9973579,0.0003256759,0.0002408009,0.000706329,0.001030326,0.0003389107],"domain_scores_gemma":[0.9973626,0.0002775436,0.0001651646,0.0009007768,0.00111452,0.0001795178],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001330197,0.0001933551,0.002146534,0.0008339412,0.00007768558,0.0001098408,0.00004593746,0.001674467,0.0007894117,0.0005569768,0.9768241,0.01661466],"study_design_scores_gemma":[0.0001893637,0.00006924656,0.009135723,0.0002777982,0.00004553483,0.0002759211,0.0003289614,0.003300371,0.002166382,0.00170614,0.9824079,0.00009674149],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001362365,0.000260407,0.0007132429,0.0001227767,0.00009666115,0.00007959452,0.9931428,0.001732074,0.002490082],"genre_scores_gemma":[0.001165496,0.00006063252,0.001499267,0.00004320922,0.000009005587,0.0000855191,0.996376,0.00007784137,0.0006829954],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02672325,"threshold_uncertainty_score":0.08939815,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01906722288432096,"score_gpt":0.2888665046634527,"score_spread":0.2697992817791318,"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."}}