{"id":"W6907408324","doi":"10.21966/rzvw-4a72","title":"3m Digital Elevation Model - Calvert Island - British Columbia - Canada","year":2015,"lang":"en","type":"dataset","venue":"Hakai Institute","topic":"","field":"","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Digital elevation model; Elevation (ballistics); Geodetic datum; Terrain; Lidar; Levelling; Shuttle Radar Topography Mission; Vegetation (pathology)","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":[0.0003412711,0.0009554802,0.0006189169,0.002221376,0.0013807,0.00230224,0.001539455,0.0004857372,0.1061832],"category_scores_gemma":[0.001366827,0.0003784342,0.0004447109,0.01075018,0.0002867231,0.0009077827,0.0008412051,0.001162527,0.04787444],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01114413,"about_ca_system_score_gemma":0.02536119,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9705375,"about_ca_topic_score_gemma":0.9787589,"domain_scores_codex":[0.999508,0.00002762698,0.00003129186,0.00007510924,0.0002582576,0.00009971076],"domain_scores_gemma":[0.9979982,0.00003778668,0.0000352177,0.00007551482,0.001761528,0.00009185907],"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":[0.00009242827,0.00003379853,0.005144911,0.0003069724,0.00003447516,0.0001360411,0.0002384915,0.002698378,0.0005415314,0.003858093,0.9393666,0.04754832],"study_design_scores_gemma":[0.00007286992,0.00000609145,0.02097632,0.0002738535,0.00002483112,0.00005498616,0.0005348617,0.004875311,0.0003953791,0.0008890203,0.9718302,0.00006625074],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.003228032,0.0003107539,0.003874697,0.0003944719,0.0001109046,0.0003260729,0.8886224,0.001517294,0.1016153],"genre_scores_gemma":[0.02406923,0.001147358,0.0159374,0.0002346337,0.00002049387,0.0007606643,0.867986,0.0009089576,0.08893529],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1061832,"threshold_uncertainty_score":0.3552182,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01891664020100696,"score_gpt":0.2255862069807063,"score_spread":0.2066695667796993,"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."}}