{"id":"W6901831676","doi":"10.60692/4nb3e-e2242","title":"Carbon footprint of grain production in China","year":2017,"lang":"en","type":"article","venue":"Greater South Information System","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Carbon footprint; Straw; Greenhouse gas; Irrigation; Life-cycle assessment; Agriculture; Carbon sequestration; Carbon fibers; Production (economics)","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":[0.0003854177,0.0004345267,0.0001530221,0.001432437,0.0003325538,0.0005772923,0.0001933752,0.0002021329,0.0004973905],"category_scores_gemma":[0.0002400347,0.0001080423,0.0004044134,0.002182385,0.000219918,0.0003756394,0.0004039509,0.0001001913,0.00005612301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002604853,"about_ca_system_score_gemma":0.001653527,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1113144,"about_ca_topic_score_gemma":0.1238995,"domain_scores_codex":[0.9998063,0.00002552591,0.00001469733,0.00003520447,0.00007802554,0.00004025606],"domain_scores_gemma":[0.9998344,0.00002311088,0.00004015612,0.00001923341,0.0000641044,0.00001890707],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002538111,0.0000715791,0.857146,0.0002296794,0.0002579719,0.0007837185,0.0004207542,0.04707216,0.01125599,0.002288936,0.001479589,0.07873992],"study_design_scores_gemma":[0.00001077,0.00005515547,0.9676756,0.00002009919,0.0000718397,0.00009197923,0.0002853072,0.02325552,0.003658072,0.0007421247,0.004108371,0.00002513163],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934321,0.0005133786,0.001119065,0.00009518909,0.000005559671,0.00001644924,0.001256924,0.00003596881,0.003525438],"genre_scores_gemma":[0.9978144,0.0002440469,0.0005129775,0.00002150373,0.000002124498,0.00001226357,0.0008110111,0.000004512028,0.0005770455],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1113144,"threshold_uncertainty_score":0.2213329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01232780044698591,"score_gpt":0.1943764293437367,"score_spread":0.1820486288967507,"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."}}