{"id":"W6963678236","doi":"10.20383/103.01254","title":"Lidar-based Canopy Gap Fraction for the Eastern Slopes Headwaters of Alberta, circa 2022","year":2025,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Transect; Canopy; Terrain; Hydrology (agriculture); Lidar; Digital elevation model; Point cloud; Multispectral Scanner","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004259337,0.001364499,0.0005849813,0.002796164,0.0008735391,0.001327338,0.001801236,0.0007876892,0.01110175],"category_scores_gemma":[0.001056847,0.0005741825,0.0005170698,0.005144729,0.0004064181,0.0003956949,0.0007017148,0.0007797769,0.007428597],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005456679,"about_ca_system_score_gemma":0.007490444,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8860755,"about_ca_topic_score_gemma":0.9524813,"domain_scores_codex":[0.9996932,0.000012212,0.00001179173,0.00007502879,0.0001318366,0.0000760696],"domain_scores_gemma":[0.9993765,0.00004742044,0.00004109576,0.00007624026,0.0003728071,0.00008603905],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001664967,0.00009270647,0.02756805,0.000533406,0.0001040721,0.000183045,0.0002953452,0.005710339,0.0007075288,0.001567297,0.9424511,0.02062057],"study_design_scores_gemma":[0.0002157847,0.0000202031,0.1326949,0.0004024084,0.00007186643,0.0001487241,0.0008818181,0.008596834,0.001522673,0.001748908,0.8536029,0.00009293894],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.004610304,0.0001246786,0.0002412672,0.00005495439,0.00001652124,0.00001930564,0.9927014,0.0004549664,0.001776548],"genre_scores_gemma":[0.00435719,0.00005104731,0.0007081603,0.00001363072,0.00000243453,0.00002427367,0.9935489,0.00003872063,0.001255617],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1139245,"threshold_uncertainty_score":0.2291908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0433328757975248,"score_gpt":0.338500166564586,"score_spread":0.2951672907670612,"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."}}