{"id":"W4393979545","doi":"10.53555/sfs.v8i3.2438","title":"Digitalization of Agriculture in India: Advocating for Doubling Farmers' Income","year":2022,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Digitalization and Economic Development in Agriculture","field":"Business, Management and Accounting","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Agricultural economics; Economics; Geography","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002296419,0.00008074298,0.0002055481,0.0004055776,0.0001366012,0.0002775106,0.000338031,0.00002555126,0.00006115331],"category_scores_gemma":[0.0004484304,0.0000614139,0.00004259771,0.001577395,0.00006003652,0.002299507,0.0001120264,0.00008710515,4.938622e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006256036,"about_ca_system_score_gemma":0.0000683485,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001275847,"about_ca_topic_score_gemma":0.0002426705,"domain_scores_codex":[0.998854,0.0000221113,0.0006161691,0.0001135967,0.0002472042,0.0001469421],"domain_scores_gemma":[0.9989185,0.0001078986,0.0007573719,0.00003378055,0.0001751018,0.000007356249],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002449615,0.00005446599,0.9905134,0.00003874837,0.000004901832,0.000001197511,0.0002365473,0.005867453,0.0000221229,0.000992942,0.00176031,0.0004834367],"study_design_scores_gemma":[0.0004948316,0.00003334667,0.9804946,0.00005691755,0.000002950718,0.000004373035,0.005017485,0.0002151478,0.00001665878,0.0009555657,0.01257872,0.000129361],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9898019,0.00004854348,0.0001074407,0.0003332414,0.0006677678,0.0001483995,0.000008732652,0.000006092481,0.00887783],"genre_scores_gemma":[0.9993684,0.0000078836,0.0001981211,0.0002143764,0.00007529968,0.000008135344,0.00003344392,0.000004033725,0.00009028664],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01081841,"threshold_uncertainty_score":0.2676041,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07679932606107316,"score_gpt":0.2353093652517949,"score_spread":0.1585100391907218,"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."}}