{"id":"W4242592695","doi":"10.32920/ryerson.14644140.v1","title":"A Laser Scanner And Void Visualizer For Use In A Search And Rescue Environment","year":2021,"lang":"en","type":"preprint","venue":"","topic":"3D Surveying and Cultural Heritage","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Theodolite; Laser scanning; Scanner; Computer science; Urban search and rescue; Explosive material; Situation awareness; Identification (biology); Computer vision; Artificial intelligence; Laser; Engineering; Aerospace engineering; Optics; Mobile robot; Cartography; Geography; Robot","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":[0.0003207349,0.0004094995,0.0003421768,0.0004771909,0.0003095619,0.0004879101,0.0007300763,0.0007302138,0.01170135],"category_scores_gemma":[0.0007634785,0.0003134078,0.0004218425,0.0003550871,0.0002615088,0.0007158379,0.0009475649,0.0004652292,0.00172463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001571312,"about_ca_system_score_gemma":0.0006013383,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009419655,"about_ca_topic_score_gemma":0.002153351,"domain_scores_codex":[0.9997969,0.00002223249,0.000005450072,0.00003596602,0.0001146285,0.00002475438],"domain_scores_gemma":[0.999705,0.0001267619,0.00002712471,0.00005914295,0.00004572649,0.00003607291],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.000846055,0.0003337099,0.01018275,0.0008223737,0.00006481688,0.00154928,0.001800398,0.03320902,0.4598078,0.007704385,0.04659513,0.4370843],"study_design_scores_gemma":[0.0004308574,0.001655036,0.03403429,0.0002553451,0.0001241164,0.004924035,0.001225648,0.3158635,0.3799289,0.005588711,0.2555457,0.0004239857],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.3409845,0.0004154058,0.5813429,0.0008383477,0.0002005836,0.0006256566,0.006090533,0.0484853,0.02101671],"genre_scores_gemma":[0.6164238,0.0003397785,0.3614819,0.0002403272,0.00003020936,0.0006039118,0.003531973,0.002795639,0.01455244],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01170135,"threshold_uncertainty_score":0.03914487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05471473575058436,"score_gpt":0.2604114478527283,"score_spread":0.2056967121021439,"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."}}