{"id":"W2073209492","doi":"10.1109/ssrr.2013.6719364","title":"Toward the automatic detection of access holes in disaster rubble","year":2013,"lang":"en","type":"article","venue":"","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Rubble; Computer science; Traverse; Set (abstract data type); Engineering; Civil engineering; Geography; Cartography","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":[0.0002808518,0.0004057765,0.000630628,0.0019155,0.0003257503,0.0006050391,0.0007752395,0.0006426839,0.0005099956],"category_scores_gemma":[0.001382349,0.0003049629,0.0002771383,0.0006992715,0.0004650814,0.0009132757,0.001288778,0.0003989027,0.0003019768],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001916196,"about_ca_system_score_gemma":0.0003422332,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002081647,"about_ca_topic_score_gemma":0.003340869,"domain_scores_codex":[0.9996507,0.00003986815,0.00001266441,0.00008441899,0.000140822,0.00007151911],"domain_scores_gemma":[0.999418,0.0001284208,0.0001114469,0.00009909738,0.0001955578,0.00004758595],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004748965,0.0002419689,0.04179193,0.0003026518,0.00005630816,0.0006302251,0.000741385,0.02904678,0.3162516,0.002519747,0.004856575,0.603086],"study_design_scores_gemma":[0.00003995884,0.0003388549,0.05368121,0.00004350342,0.00003684616,0.001273038,0.0007811961,0.8463517,0.09018729,0.002823017,0.004390217,0.00005312764],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5356671,0.0003506886,0.4568362,0.0001211543,0.00004098595,0.0001319985,0.0002751083,0.004048666,0.002528033],"genre_scores_gemma":[0.8751072,0.0001028998,0.1238367,0.00003032266,0.00001066608,0.00003068091,0.0002524873,0.00005562254,0.0005734584],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002081647,"threshold_uncertainty_score":0.004139006,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02179824468942076,"score_gpt":0.2192946198059765,"score_spread":0.1974963751165558,"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."}}