{"id":"W2121758370","doi":"10.1109/cvpr.2004.348","title":"Forestry Scene Geometry Estimation Via Statistical Learning","year":2005,"lang":"en","type":"article","venue":"","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Computer science; Artificial intelligence; Context (archaeology); Probabilistic logic; Markov chain Monte Carlo; Maxima and minima; Tree (set theory); Graphical model; Algorithm; Computer vision; Mathematics; Bayesian probability; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001017921,0.0006049423,0.001028408,0.001542022,0.0003289275,0.0007335872,0.001210221,0.0007673849,0.0008006392],"category_scores_gemma":[0.004868889,0.0006553034,0.0007844166,0.001114531,0.0007165208,0.001407659,0.000775056,0.0008431808,0.0003783332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007024592,"about_ca_system_score_gemma":0.0008766772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00569299,"about_ca_topic_score_gemma":0.006624628,"domain_scores_codex":[0.9993646,0.0001954437,0.00003059007,0.0001883605,0.0001692528,0.00005169605],"domain_scores_gemma":[0.9981872,0.001161892,0.0002060586,0.0001949569,0.0002080617,0.00004165092],"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":[0.00006007903,0.00004779163,0.001602364,0.00003393096,0.00004595287,0.00004014745,0.00003194881,0.864306,0.00260869,0.003917245,0.0004753954,0.1268303],"study_design_scores_gemma":[0.000003807641,0.00000677629,0.0002660313,0.000001440517,0.00000254597,0.00001366728,0.00000369232,0.9951934,0.000584733,0.003812469,0.0001069225,0.00000444695],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0172773,0.00005923142,0.9817532,0.00006094687,0.000004615753,0.00001533392,0.00004651203,0.0005326839,0.0002502284],"genre_scores_gemma":[0.5711054,0.0001852302,0.4270807,0.00009281612,0.0000451127,0.00008845662,0.0006169002,0.00009718552,0.0006882467],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00569299,"threshold_uncertainty_score":0.0113197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006672904268680674,"score_gpt":0.2435298222528849,"score_spread":0.2368569179842042,"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."}}