{"id":"W7051522403","doi":"","title":"OBJECT-BASED URBAN TREE COVER EXTRACTION FROM HIGH SPATIAL RESOLUTION OPTICAL AND LIDAR IMAGERY: TECHNIQUES AND DATA INTEGRATION","year":2010,"lang":"en","type":"article","venue":"Scholarship@Western (Western University)","topic":"Magnetic confinement fusion research","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Orthophoto; Lidar; Tree (set theory); Cover (algebra); Extraction (chemistry); Displacement (psychology); Image resolution; Urban area; Measure (data warehouse)","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002902679,0.0002994136,0.0002631224,0.0009601438,0.0002351454,0.0005552581,0.0003349274,0.000245741,0.0008123867],"category_scores_gemma":[0.000469103,0.000223352,0.0003256339,0.0009332503,0.0001441202,0.0005793182,0.0003015461,0.0002103128,0.0004172822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000194623,"about_ca_system_score_gemma":0.0002709789,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002815929,"about_ca_topic_score_gemma":0.006884919,"domain_scores_codex":[0.9998399,0.00001468826,0.000009315172,0.00003061495,0.00008760142,0.00001787946],"domain_scores_gemma":[0.9998491,0.00003825055,0.00002167255,0.00002362425,0.000061609,0.000005727984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001061897,0.0001126075,0.01164823,0.0002529086,0.00007036272,0.0001297399,0.0003403546,0.03335255,0.2502936,0.0015881,0.001275314,0.70083],"study_design_scores_gemma":[0.00003242334,0.0001432041,0.08040351,0.00003626736,0.0001016396,0.0006031404,0.0003984191,0.6220021,0.2836393,0.001903882,0.01064385,0.0000922924],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.2669646,0.0003114893,0.7282151,0.00006458947,0.0000203866,0.0001141448,0.000401967,0.001617902,0.00228994],"genre_scores_gemma":[0.3697435,0.0003821715,0.626815,0.00002034865,0.00001422908,0.0001041582,0.0008356823,0.0001038219,0.001981033],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002815929,"threshold_uncertainty_score":0.005599022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0463756483697976,"score_gpt":0.3141101616893996,"score_spread":0.267734513319602,"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."}}