{"id":"W2095958845","doi":"10.1016/j.agrformet.2004.09.006","title":"Methodology comparison for canopy structure parameters extraction from digital hemispherical photography in boreal forests","year":2005,"lang":"en","type":"article","venue":"Agricultural and Forest Meteorology","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":436,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto; Natural Resources Canada","funders":"","keywords":"TRAC; Zenith; Leaf area index; Remote sensing; Radiance; Environmental science; Black spruce; Pixel; Bidirectional reflectance distribution function; Sky; Canopy; Taiga; Geography; Optics; Meteorology; Physics; Computer science; Ecology","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":[0.003095945,0.0004576079,0.0004147168,0.001908245,0.0004467272,0.0009414428,0.000618569,0.0004900376,0.001683431],"category_scores_gemma":[0.003532998,0.000328387,0.0006130011,0.001001275,0.0001341176,0.0006779937,0.0005068818,0.0002091515,0.00046741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004001138,"about_ca_system_score_gemma":0.0006345874,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005037223,"about_ca_topic_score_gemma":0.007464822,"domain_scores_codex":[0.9991502,0.000264425,0.0001025753,0.0001854365,0.0002405212,0.00005699118],"domain_scores_gemma":[0.9979214,0.0007765569,0.0001097777,0.0001939571,0.0009512696,0.00004706192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0008864285,0.0002544708,0.04069512,0.000687606,0.0006288621,0.0001792657,0.0004272526,0.01131588,0.09792043,0.001457077,0.001710003,0.8438376],"study_design_scores_gemma":[0.0004615699,0.001159575,0.2693523,0.0002249437,0.00127486,0.002478795,0.001327698,0.4931968,0.2013968,0.004015883,0.02484967,0.0002612105],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1914909,0.001592863,0.8018699,0.0000820466,0.00008104891,0.0002689707,0.0009306932,0.001558894,0.002124768],"genre_scores_gemma":[0.3857377,0.0009614953,0.6090989,0.00008413085,0.00002871559,0.0003166801,0.001858201,0.0002180032,0.00169629],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.005037223,"threshold_uncertainty_score":0.0163731,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01733213150991286,"score_gpt":0.2574334379233497,"score_spread":0.2401013064134369,"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."}}