{"id":"W2023592410","doi":"10.5558/tfc85859-6","title":"Forest inventory research at the Canadian Wood Fibre Centre: Notes from a research coordination workshop, June 3–4, 2009, Pointe Claire, QC","year":2009,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Natural Resources Canada; World Wildlife Fund Canada; Canadian Forest Service","funders":"","keywords":"Forest inventory; Mandate; Multispectral image; Computer science; Business; Environmental resource management; Forestry; Environmental science; Operations research; Geography; Remote sensing; Forest management; Engineering; Political science","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001905215,0.0001565634,0.0001194406,0.00007579764,0.002692847,0.0001979042,0.0008665381,0.0001550398,0.001078895],"category_scores_gemma":[0.000280965,0.0001041292,0.00007653429,0.001013385,0.001087273,0.0001764808,0.0002870118,0.0009138294,0.002778427],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00201496,"about_ca_system_score_gemma":0.0002461357,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.2372158,"about_ca_topic_score_gemma":0.8612444,"domain_scores_codex":[0.9968957,0.000474491,0.0002260221,0.0004542481,0.0009660889,0.0009834161],"domain_scores_gemma":[0.9978864,0.000574763,0.00005725016,0.00111875,0.00006749024,0.0002953258],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008295358,0.000154249,0.007412883,0.000005387227,0.00003012117,0.00002035179,0.003092576,0.00700841,0.004796085,0.002360487,0.9374843,0.03755215],"study_design_scores_gemma":[0.000835861,0.0001422469,0.2252023,0.0001286687,0.00002865384,0.00002890002,0.001378684,0.02778975,0.005257984,0.05167485,0.6870723,0.0004597817],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8776943,0.0005146637,0.00003321646,0.1046239,0.0001012357,0.0007051179,0.00003253976,0.00005184105,0.01624321],"genre_scores_gemma":[0.9836533,0.00003088113,0.00008623335,0.0003612872,0.000237436,0.000009332877,0.00006621697,0.00002264386,0.01553267],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6240286,"threshold_uncertainty_score":0.9998342,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04517345571306042,"score_gpt":0.3141696718415323,"score_spread":0.2689962161284719,"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."}}