{"id":"W4391220989","doi":"10.3390/cli12020015","title":"Net Zero Dairy Farming—Advancing Climate Goals with Big Data and Artificial Intelligence","year":2024,"lang":"en","type":"article","venue":"Climate","topic":"Agriculture Sustainability and Environmental Impact","field":"Environmental Science","cited_by":39,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Big data; Zero (linguistics); Agriculture; Environmental science; Dairy farming; Environmental resource management; Meteorology; Agricultural science; Computer science; Geography; Data mining","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005423814,0.0002295233,0.0001811068,0.00002710226,0.0002610075,0.0001904161,0.0003314426,0.00006958798,0.0004028166],"category_scores_gemma":[0.00003716393,0.000157285,0.00002816436,0.0002563421,0.0004176373,0.0006956367,0.001111121,0.0002061018,0.0004835718],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001766632,"about_ca_system_score_gemma":0.000008513155,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001067543,"about_ca_topic_score_gemma":0.0002074202,"domain_scores_codex":[0.9981064,0.00004260889,0.000265636,0.0007020491,0.0002400767,0.0006432397],"domain_scores_gemma":[0.9991636,0.00008506113,0.00004966904,0.000520696,0.000002549421,0.0001784639],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0002813472,0.0003688001,0.1038224,0.0008143455,0.00008091647,0.0006498495,0.005412985,0.008496709,0.0227692,0.001536301,0.004095485,0.8516717],"study_design_scores_gemma":[0.0008409863,0.002848714,0.423839,0.001722144,0.001011482,0.001763427,0.03439626,0.1524869,0.01705854,0.04863625,0.3089365,0.006459758],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.988376,0.0005009141,0.005804383,0.0008067001,0.0003000871,0.0003679679,0.0001897835,0.0001864331,0.003467684],"genre_scores_gemma":[0.9977342,0.0005880733,0.001190091,0.0001918158,0.00009854687,0.00001063827,0.00007983283,0.00002491557,0.00008181256],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8452119,"threshold_uncertainty_score":0.6413896,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02906195632127333,"score_gpt":0.2710146401755743,"score_spread":0.241952683854301,"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."}}