{"id":"W2072334158","doi":"10.1139/x08-037","title":"Estimation of species-specific diameter distributions using airborne laser scanning and aerial photographs","year":2008,"lang":"en","type":"article","venue":"Canadian Journal of Forest Research","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":146,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Weibull distribution; Picea abies; Scots pine; Deciduous; Laser scanning; Environmental science; Remote sensing; Forestry; Mathematics; Statistics; Pinus <genus>; Geography; Ecology; Laser; Botany; Biology; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005206399,0.0000628674,0.0001236373,0.0002455158,0.0004555287,0.00003664046,0.0001438862,0.00004454505,0.0002361711],"category_scores_gemma":[0.000120381,0.00005798806,0.00005140941,0.0005693134,0.0009833087,0.0001373443,0.00002276983,0.0002390483,0.00001032285],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002263214,"about_ca_system_score_gemma":0.0002287507,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01117889,"about_ca_topic_score_gemma":0.01158286,"domain_scores_codex":[0.9989676,0.00007500997,0.0002383351,0.0001101044,0.000321229,0.0002876616],"domain_scores_gemma":[0.9992037,0.0000771992,0.00008746929,0.0001517419,0.00007686001,0.0004030292],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001114937,0.0001355458,0.8384798,0.00003031512,0.00008092124,0.0003759343,0.004642845,0.04723496,0.03744239,0.001117347,0.02269537,0.04765306],"study_design_scores_gemma":[0.0003944998,0.0001360264,0.9749331,0.00007308787,0.00001068255,0.000466071,0.000225036,0.004270917,0.006515415,0.001244576,0.01159984,0.0001307063],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9950879,0.0000796914,0.00270624,0.0001375866,0.00005645191,0.00009581247,0.00002148681,0.00000177852,0.001813107],"genre_scores_gemma":[0.9958355,0.00003663178,0.003968277,0.000004771753,0.00006986252,4.196771e-7,0.000004859055,0.000007657026,0.00007195066],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1364533,"threshold_uncertainty_score":0.9954057,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05947161543019237,"score_gpt":0.2929954648541119,"score_spread":0.2335238494239196,"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."}}