{"id":"W6969560208","doi":"10.5683/sp3/hdexqw","title":"Total mercury, methylmercury, nitrogen, carbon, hydrogen, and sulfur concentrations in a degrading lithalsa field near Kangiqsualujjuaq (Nunavik, Canada)","year":2025,"lang":"en","type":"dataset","venue":"Borealis","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Thermokarst; Permafrost; Methylmercury; Sulfur; Mercury (programming language); Total organic carbon; Organic matter; Hydrology (agriculture)","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":[0.0001616014,0.0004094706,0.0003193844,0.001263931,0.000941594,0.000630701,0.0009874575,0.0002591854,0.00369852],"category_scores_gemma":[0.0004445778,0.0002060424,0.0003875173,0.003816353,0.0003258845,0.0001925054,0.0006333668,0.000306963,0.0009717484],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00944197,"about_ca_system_score_gemma":0.01182693,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9866793,"about_ca_topic_score_gemma":0.9929836,"domain_scores_codex":[0.9998116,0.000007418571,0.00001190893,0.00005182424,0.00005919824,0.00005803176],"domain_scores_gemma":[0.9992084,0.00003218872,0.00005732478,0.00003189619,0.0005593835,0.0001108781],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006119579,0.0001129557,0.8756941,0.0009303466,0.0002949684,0.0004771058,0.001821511,0.003307302,0.006486062,0.0005180466,0.07834849,0.03139722],"study_design_scores_gemma":[0.00005393357,0.00003139797,0.9664361,0.0001270417,0.00004844099,0.0000671008,0.002903652,0.001351334,0.0008901369,0.00006508088,0.02798433,0.00004150544],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.4292974,0.0004902559,0.0001674241,0.0001908937,0.00002049644,0.00008338277,0.565033,0.0001323528,0.004584752],"genre_scores_gemma":[0.4552409,0.0006776321,0.001438889,0.0001491096,0.00000844529,0.0001366252,0.5336297,0.00005446788,0.008664258],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.01332074,"threshold_uncertainty_score":0.0685066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01166377515462006,"score_gpt":0.2606075795826692,"score_spread":0.2489438044280491,"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."}}