{"id":"W6950625654","doi":"10.5281/zenodo.7953872","title":"Data of article: \"Drivers of contrasting boreal understory vegetation in coniferous and broadleaf deciduous alternative states\"","year":2023,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Tree-ring climate responses","field":"Earth and Planetary Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Moncton; Université du Québec à Montréal; Université du Québec en Abitibi-Témiscamingue","funders":"","keywords":"Understory; Deciduous; Boreal; Vegetation (pathology); Taiga; Plant community","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":[0.0009185353,0.0004542031,0.00042843,0.001067011,0.0003926638,0.0009993616,0.000773599,0.0004287687,0.1958443],"category_scores_gemma":[0.005953941,0.0002635733,0.0005100488,0.001843358,0.0002026787,0.0008582473,0.000865602,0.0006250431,0.05253537],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005282558,"about_ca_system_score_gemma":0.0009418269,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01838057,"about_ca_topic_score_gemma":0.03620472,"domain_scores_codex":[0.9992284,0.000123545,0.00006121567,0.0001844066,0.0003350171,0.00006751934],"domain_scores_gemma":[0.9956908,0.001758519,0.0005620876,0.0005324734,0.001131333,0.0003248612],"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":[0.0003371276,0.00005245224,0.01987288,0.0006739084,0.00007501587,0.00004142228,0.0002275609,0.0006168419,0.001085754,0.001842608,0.9583219,0.01685238],"study_design_scores_gemma":[0.0001915602,0.00006197906,0.2099786,0.0002776478,0.00009012046,0.0001177406,0.0004819237,0.0009210276,0.00253806,0.002831652,0.7824391,0.00007054658],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.005707884,0.00009719072,0.000947293,0.000396268,0.000266644,0.00005655293,0.98016,0.0008008289,0.01156745],"genre_scores_gemma":[0.03842434,0.0002168849,0.004135307,0.0003341745,0.0001824837,0.0004206673,0.9279614,0.002202252,0.02612258],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1958443,"threshold_uncertainty_score":0.6551644,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06874053490575904,"score_gpt":0.2666067466413806,"score_spread":0.1978662117356216,"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."}}