{"id":"W2180136417","doi":"10.3390/rs71115605","title":"Automatic Object Extraction from Electrical Substation Point Clouds","year":2015,"lang":"en","type":"article","venue":"Remote Sensing","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canada Foundation for Innovation","keywords":"Point cloud; Computer science; Laser scanning; Key (lock); Lidar; Circuit breaker; Reliability (semiconductor); Scanner; Real-time computing; Remote sensing; Power (physics); Laser; Electrical engineering; Artificial intelligence; Engineering; Geology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0003421757,0.001215476,0.001076411,0.004782148,0.0005022939,0.001133168,0.0009373226,0.000986137,0.001104231],"category_scores_gemma":[0.0009228297,0.0004826942,0.0009044204,0.003103576,0.0002702768,0.001282279,0.001008532,0.0005359039,0.001363153],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003931346,"about_ca_system_score_gemma":0.0007379544,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006070158,"about_ca_topic_score_gemma":0.007627877,"domain_scores_codex":[0.9994138,0.00003940606,0.00004122424,0.0001488622,0.0002462423,0.0001104254],"domain_scores_gemma":[0.9995514,0.00009582705,0.00007026285,0.00009715619,0.0001629493,0.00002234226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0002583075,0.0002251481,0.01398792,0.0003091769,0.0001157695,0.0007865881,0.0001907774,0.03994244,0.1478615,0.001316274,0.00741907,0.7875869],"study_design_scores_gemma":[0.00003546202,0.0001119586,0.04867246,0.00008705071,0.0001011555,0.0008402936,0.0005149281,0.8074459,0.1261606,0.003298349,0.01266553,0.00006628686],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2760434,0.000974558,0.7058168,0.0001927391,0.0001129504,0.0004377008,0.003540993,0.009151193,0.003729708],"genre_scores_gemma":[0.6391287,0.0009480192,0.3464426,0.00007245924,0.00006170737,0.0002663425,0.01075371,0.0001939803,0.002132412],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.006070158,"threshold_uncertainty_score":0.01206964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01988147071106455,"score_gpt":0.2652129867875989,"score_spread":0.2453315160765343,"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."}}