{"id":"W6931554393","doi":"10.5683/sp3/cdjs5l","title":"SPATIAL AND TEMPORAL PATTERNS OF NET CARBON EXCHANGE IN THE POLAR SEMI-DESERT VEGETATION TYPE ON MELVILLE ISLAND, NUNAVUT (2013)","year":2016,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"","keywords":"Arctic; Vegetation (pathology); Permafrost; Vegetation type; Polar; Primary production; Water content; Tundra","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003432841,0.0004173185,0.0003210262,0.001192672,0.0004362337,0.000577617,0.0008349192,0.0002799255,0.001589015],"category_scores_gemma":[0.0006203339,0.000158539,0.0002901238,0.002237157,0.0002267894,0.0002154047,0.0006210196,0.0003013981,0.0008203552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001576651,"about_ca_system_score_gemma":0.0009452795,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5608093,"about_ca_topic_score_gemma":0.7551399,"domain_scores_codex":[0.9998344,0.00001878948,0.00001333149,0.00006370734,0.00003394415,0.00003571116],"domain_scores_gemma":[0.9996219,0.00003431013,0.00007804315,0.00004499979,0.0001514162,0.0000693048],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004737788,0.0001296329,0.801603,0.0004841269,0.0002749366,0.0004155483,0.0009075552,0.003554161,0.002025764,0.0006430677,0.1764187,0.01306996],"study_design_scores_gemma":[0.00003694752,0.00001244379,0.9574298,0.00008695119,0.00002668817,0.00009439389,0.0006598572,0.001844013,0.00034524,0.0000803602,0.03935545,0.00002799912],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.241721,0.0006904817,0.0001910711,0.00021602,0.00005304913,0.00002769611,0.7542672,0.0001551801,0.00267826],"genre_scores_gemma":[0.2397213,0.0003225287,0.0009717164,0.00009129375,0.00002514855,0.0001014177,0.756367,0.00004683847,0.002352728],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.4391907,"threshold_uncertainty_score":0.8835545,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01704270183157094,"score_gpt":0.2564123761581821,"score_spread":0.2393696743266112,"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."}}