{"id":"W1872081294","doi":"10.1002/rob.21590","title":"What is a Hole? Discovering Access Holes in Disaster Rubble with Functional and Photometric Attributes","year":2015,"lang":"en","type":"article","venue":"Journal of Field Robotics","topic":"Robotics and Sensor-Based Localization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Seneca Polytechnic; Toronto Metropolitan University","funders":"","keywords":"Rubble; Metric (unit); Computer science; Set (abstract data type); Search and rescue; Traverse; Artificial intelligence; Engineering; Civil engineering; Cartography; Geography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001189579,0.00009537356,0.0001719409,0.0002454353,0.00001802594,0.0002358735,0.00008001263,0.00006220143,0.00000929683],"category_scores_gemma":[0.00003623839,0.00007366051,0.00002731864,0.0003214446,0.00001845613,0.0007853583,0.0000237905,0.0001841208,9.268662e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004263147,"about_ca_system_score_gemma":0.00002637423,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005553527,"about_ca_topic_score_gemma":0.00001468601,"domain_scores_codex":[0.999338,0.0000105127,0.0002405079,0.00006524463,0.0002191463,0.0001265554],"domain_scores_gemma":[0.9995885,0.00007961904,0.00006667368,0.00007341349,0.00009784495,0.00009389182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003172737,0.0000214804,0.02824596,0.00003326277,0.00002548745,0.00002360659,0.0002928331,0.9697544,0.00006831348,0.00004842532,0.0007453373,0.0007091501],"study_design_scores_gemma":[0.005278728,0.001101977,0.04327498,0.001340254,0.0001675116,0.0003436167,0.00373793,0.9324571,0.008905272,0.001242107,0.001303479,0.0008470708],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5488104,0.001478032,0.4477485,0.001012372,0.0007578463,0.00006722358,0.00000154787,0.00001256945,0.0001115487],"genre_scores_gemma":[0.9972222,0.000652959,0.001772379,0.0001765845,0.0001183388,5.052795e-7,0.000001727592,0.00001393869,0.00004129911],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4484119,"threshold_uncertainty_score":0.3003788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03859045935320986,"score_gpt":0.2525203290909072,"score_spread":0.2139298697376973,"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."}}