{"id":"W2386958723","doi":"","title":"Response of winter wheat and cotton to climate warming in Northwest China","year":2009,"lang":"en","type":"article","venue":"Ganhan diqu nongye yanjiu","topic":"Environmental and Agricultural Sciences","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada","funders":"","keywords":"Sowing; Agronomy; Winter wheat; Environmental science; Sanjiang Plain; Cultivar; Global warming; Biology; Climate change; Ecology; Wetland","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003584404,0.0001409498,0.0001635273,0.00003828331,0.00007952271,0.00002195569,0.0001978895,0.00004156616,0.0003694535],"category_scores_gemma":[0.00001979894,0.00009641486,0.00003380542,0.0002777482,0.0001340596,0.0002617924,0.0001753424,0.00007633091,0.0001235561],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007835747,"about_ca_system_score_gemma":0.000002048541,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004983604,"about_ca_topic_score_gemma":0.001404932,"domain_scores_codex":[0.9988208,0.00005981197,0.0002209108,0.0003285146,0.0002430408,0.0003268801],"domain_scores_gemma":[0.9996358,0.00003234178,0.00005080492,0.0001288397,0.000001577582,0.0001506412],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0001935526,0.0001157073,0.4429915,0.000004167208,0.000001365712,0.00001854093,0.002240018,0.0002255046,0.5404024,0.000007442461,0.0002070857,0.01359274],"study_design_scores_gemma":[0.0001667695,0.0002895157,0.960897,0.00004065132,0.000002724641,0.00001036333,0.0002212522,0.00002948013,0.03758852,0.00005196971,0.0005520775,0.000149638],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9962177,0.00002389534,0.00000468242,0.001555327,0.00003813041,0.0001803919,0.000008937612,0.00001511191,0.001955838],"genre_scores_gemma":[0.9987998,0.00004222673,0.000420643,0.0003420656,0.00001323045,0.000003875908,0.00000301314,0.000003790357,0.0003713797],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5179056,"threshold_uncertainty_score":0.4045256,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003936153205766168,"score_gpt":0.2029210518772751,"score_spread":0.1989848986715089,"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."}}