{"id":"W6942106846","doi":"10.1371/journal.pone.0260946.g004","title":"Saskatchewan GHGs estimates in the crop sector (Mt CO2-eq) (1985–2016).","year":2021,"lang":"en","type":"other","venue":"Figshare","topic":"Mycorrhizal Fungi and Plant Interactions","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Crop; Agriculture; Crop yield; Crop production; Climate change; Productivity","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":[0.0004912447,0.0006974984,0.0002618531,0.002232036,0.0004383039,0.0007671948,0.0008890854,0.0003479596,0.01957621],"category_scores_gemma":[0.001026522,0.0002854649,0.000505425,0.006641899,0.0002642739,0.000850276,0.001051788,0.0006193143,0.005539313],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007698761,"about_ca_system_score_gemma":0.01088359,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.91561,"about_ca_topic_score_gemma":0.9620469,"domain_scores_codex":[0.9997588,0.00002903667,0.00001923771,0.00005222207,0.00008890146,0.00005191945],"domain_scores_gemma":[0.9992612,0.00004674188,0.00006127328,0.00006172223,0.0005026725,0.00006634724],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0004300058,0.00007848942,0.1425609,0.001139743,0.0006633759,0.000309204,0.0005757585,0.01092819,0.00326669,0.01642569,0.7182964,0.1053255],"study_design_scores_gemma":[0.0000682387,0.00001499051,0.4601386,0.0004342027,0.0001163566,0.00009261771,0.001455382,0.003356335,0.00307898,0.00405467,0.5270937,0.00009594068],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.04557148,0.001858236,0.001844933,0.001301317,0.0002476063,0.00006282514,0.8795531,0.000306708,0.06925379],"genre_scores_gemma":[0.3280309,0.005478217,0.008298283,0.001165971,0.00006720999,0.0002899378,0.4921801,0.0005389976,0.1639504],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.08439004,"threshold_uncertainty_score":0.169774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03622174890346913,"score_gpt":0.2343105105955164,"score_spread":0.1980887616920473,"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."}}