{"id":"W4230167959","doi":"10.22215/etd/2006-08093","title":"Impacts of radiometric corrections on empirical modelling of biophysical variables with airborne multispectral digital camera imagery","year":2006,"lang":"en","type":"dissertation","venue":"","topic":"Remote Sensing in Agriculture","field":"Environmental Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Canadian Heritage","funders":"","keywords":"Multispectral image; Remote sensing; Geography; Cartography; Computer graphics (images); Computer science","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":[0.00207246,0.0006702167,0.000409163,0.0004209039,0.00033892,0.001222202,0.0009517464,0.000881363,0.001033887],"category_scores_gemma":[0.01581061,0.0004561039,0.0007055417,0.000462571,0.0005494475,0.001242237,0.0005547561,0.0008617998,0.0002480122],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001134332,"about_ca_system_score_gemma":0.001150909,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.05697591,"about_ca_topic_score_gemma":0.03514519,"domain_scores_codex":[0.9991365,0.000410359,0.00005611814,0.0001587729,0.0001742804,0.00006405171],"domain_scores_gemma":[0.9932768,0.005326884,0.0003711796,0.0003841581,0.0005496289,0.00009125742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.00007214515,0.0000561837,0.005740515,0.00002758474,0.00004189605,0.00002769744,0.00003027957,0.977845,0.0008054574,0.0003070164,0.0002304577,0.01481587],"study_design_scores_gemma":[0.000007349344,0.00001975933,0.001616147,0.000004833562,0.0000109395,0.000007852967,0.00001215826,0.9970999,0.0009163494,0.0001636361,0.0001348753,0.000006222775],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9110755,0.0006951713,0.08228247,0.0008570906,0.0001411798,0.00007081265,0.0004150151,0.001156148,0.003306735],"genre_scores_gemma":[0.9776924,0.0001677845,0.02071925,0.00005643849,0.00002172211,0.0000301602,0.0002014614,0.0001050894,0.001005761],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05697591,"threshold_uncertainty_score":0.1132885,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0108633367709889,"score_gpt":0.2321782988442107,"score_spread":0.2213149620732218,"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."}}