{"id":"W3195364802","doi":"10.3390/rs13163297","title":"A Novel Framework for Rapid Detection of Damaged Buildings Using Pre-Event LiDAR Data and Shadow Change Information","year":2021,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Impact of Light on Environment and Health","field":"Environmental Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada","funders":"","keywords":"Shadow (psychology); Event (particle physics); Computer science; Lidar; Remote sensing; Environmental science; Geology","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":[0.0004487087,0.00010116,0.0001428281,0.00003831197,0.0001721783,0.00003396644,0.00007475619,0.0000899026,0.00002290348],"category_scores_gemma":[0.0001709861,0.0001052244,0.00002702945,0.0001344014,0.00005654457,0.0007420159,0.0002271773,0.0001113083,0.000003071642],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001316404,"about_ca_system_score_gemma":0.00001602939,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004413188,"about_ca_topic_score_gemma":0.00004043614,"domain_scores_codex":[0.9991012,0.00002726645,0.0002338854,0.0001954997,0.0002036124,0.0002385557],"domain_scores_gemma":[0.9993343,0.00006272497,0.0001873005,0.0003261839,0.000008807986,0.00008063723],"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":[0.00004715318,0.00002213856,0.0006939559,0.0001056071,0.00001191528,9.759681e-7,0.001997873,0.00006467099,0.4639281,0.00001370515,0.000004923115,0.5331089],"study_design_scores_gemma":[0.001279259,0.0002225556,0.1474181,0.0005557211,0.0001232221,0.0001561829,0.0007823754,0.6959278,0.1411408,0.001005338,0.01087718,0.0005114354],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5607816,0.00004422614,0.4386634,0.0001717515,0.00007105711,0.0001887305,0.0000117795,0.00001000298,0.00005740849],"genre_scores_gemma":[0.7667526,0.00007006621,0.2328227,0.0002505263,0.00006636603,2.823697e-8,0.00002271322,0.000009088321,0.000005888261],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6958631,"threshold_uncertainty_score":0.4290927,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05758038049420901,"score_gpt":0.3052015251042159,"score_spread":0.2476211446100069,"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."}}