{"id":"W7119092715","doi":"10.5061/dryad.3ffbg79z4","title":"Data from: Warming-induced effects on microbial communities and nitrogen cycling capacity in tundra litter","year":2025,"lang":"en","type":"dataset","venue":"Open MIND","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Tundra; Nitrogen cycle; Ecosystem; Litter; Cycling; Abundance (ecology); Dominance (genetics); Vegetation (pathology); Abiotic component","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.001386519,0.0006044449,0.0006540907,0.001637493,0.000770914,0.001303576,0.0006884571,0.0006080626,0.04664036],"category_scores_gemma":[0.002787427,0.0002696431,0.0005568784,0.002757716,0.0002763075,0.0006987342,0.001227686,0.0007112398,0.01851884],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005536096,"about_ca_system_score_gemma":0.001271346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01368908,"about_ca_topic_score_gemma":0.02778977,"domain_scores_codex":[0.998884,0.0001242702,0.0001483432,0.0002832124,0.0004129021,0.0001471449],"domain_scores_gemma":[0.9971036,0.0005776185,0.0003967766,0.0006021541,0.0009944249,0.000325374],"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":[0.00464059,0.0008872499,0.2096439,0.004793406,0.0009383837,0.0007646968,0.001928309,0.002586783,0.07458068,0.001814663,0.5860807,0.1113406],"study_design_scores_gemma":[0.0004273451,0.0003501216,0.4453383,0.0004741321,0.000242999,0.0001946128,0.0006274406,0.001590267,0.01810274,0.001032749,0.5314946,0.0001245567],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.03641638,0.0001926958,0.0009803488,0.0002363783,0.0001359492,0.0001009848,0.9541864,0.001079676,0.00667104],"genre_scores_gemma":[0.03517468,0.0002594386,0.003177475,0.0002135633,0.00005087893,0.0003081653,0.9552274,0.0002777311,0.005310704],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.04664036,"threshold_uncertainty_score":0.1560276,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1483416347584999,"score_gpt":0.3485632218020061,"score_spread":0.2002215870435061,"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."}}