{"id":"W2999660945","doi":"10.5558/tfc2019-024","title":"The Petawawa Research Forest: Establishment of a remote sensing supersite","year":2019,"lang":"en","type":"article","venue":"The Forestry Chronicle","topic":"Remote Sensing and LiDAR Applications","field":"Environmental Science","cited_by":20,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ministry of Natural Resources and Forestry; Canadian Forest Service","funders":"","keywords":"Remote sensing; Benchmarking; Pace; Download; Environmental science; Canopy; Lidar; Computer science; Geography; World Wide Web; Business","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001201363,0.00008970613,0.0000938642,0.00001796818,0.0005542034,0.00006356337,0.0004695294,0.00004506891,0.0001325539],"category_scores_gemma":[0.00004622827,0.00005187704,0.00006723418,0.0003970886,0.000589376,0.00008366942,0.0003303784,0.0002824357,0.0008116217],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001930138,"about_ca_system_score_gemma":0.00004312858,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002136712,"about_ca_topic_score_gemma":0.0007460042,"domain_scores_codex":[0.9985096,0.000126912,0.0001820923,0.0002260332,0.000534027,0.0004213601],"domain_scores_gemma":[0.9986116,0.0002998182,0.00006070114,0.000943226,0.00002575634,0.00005886327],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000306974,0.0001974294,0.0506659,0.00009312521,0.0001591029,0.00001641605,0.01041607,0.04399398,0.1275879,0.007292045,0.06298647,0.6962847],"study_design_scores_gemma":[0.001279739,0.000413577,0.1959682,0.0001316442,0.00004718515,0.0001141609,0.004201166,0.3119281,0.02705656,0.02862212,0.4297473,0.0004903392],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9676336,0.0001067792,0.0002789087,0.002031843,0.0000729384,0.0003791214,0.000001813995,0.00002369335,0.02947131],"genre_scores_gemma":[0.9958742,0.00003532625,0.0009528589,0.00004495655,0.00004767336,3.246871e-7,0.000002310745,0.00001476403,0.003027586],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6957943,"threshold_uncertainty_score":0.9999664,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02007826028652271,"score_gpt":0.2762048557009328,"score_spread":0.2561265954144101,"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."}}