{"id":"W2083031250","doi":"10.1139/x10-085","title":"Sampling gap fraction and size for estimating leaf area and clumping indices from hemispherical photographs","year":2010,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Helsingin Yliopisto","keywords":"Leaf area index; Sampling (signal processing); Canopy; Azimuth; Remote sensing; Environmental science; Fraction (chemistry); Fetch; Tree canopy; Mathematics; Geometry; Ecology; Geography; Geology; Optics; Physics; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"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":[0.001623258,0.0002863901,0.0002831673,0.0007745491,0.0002048762,0.0003063289,0.0004656205,0.0003235423,0.0004269661],"category_scores_gemma":[0.006263272,0.0002549838,0.0002753345,0.0006379304,0.0002646478,0.0006390029,0.000287013,0.0002256765,0.0001454282],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002415119,"about_ca_system_score_gemma":0.0002669982,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002783963,"about_ca_topic_score_gemma":0.006073805,"domain_scores_codex":[0.9993443,0.0003163434,0.00003293325,0.0001035208,0.0001731421,0.00002979897],"domain_scores_gemma":[0.997437,0.001675912,0.0002488996,0.0003626451,0.0002168435,0.00005872252],"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":[0.0008713574,0.0001757351,0.1570962,0.00040575,0.0001620982,0.0002686362,0.0006702042,0.08965608,0.2150092,0.003147582,0.0006944448,0.5318426],"study_design_scores_gemma":[0.00006493262,0.0003300376,0.2670058,0.00004891238,0.0001054378,0.0007392149,0.0002815111,0.6387098,0.0895867,0.00193893,0.00110829,0.0000804962],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5642612,0.0002902549,0.4338593,0.00002794771,0.00001068937,0.000119794,0.0002238342,0.000431506,0.0007754755],"genre_scores_gemma":[0.6321865,0.0001211815,0.3673105,0.00001244552,0.000004907569,0.00008999158,0.0001570189,0.00003392244,0.00008352958],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002783963,"threshold_uncertainty_score":0.008584738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04462934144401116,"score_gpt":0.3127189641109336,"score_spread":0.2680896226669224,"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."}}