{"id":"W2948134094","doi":"","title":"Impact assessment of rabi Onion variety Agrifound Light Red (AFLR) through OFTs in Sidhi District of Madhya Pradesh","year":2019,"lang":"en","type":"article","venue":"Journal of Emerging Technologies and Innovative Research","topic":"Agricultural Economics and Practices","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Agriculture; Agricultural science; Productivity; Yield (engineering); Mathematics; Quarter (Canadian coin); Non-invasive ventilation; Toxicology; Agricultural economics; Geography; Business; Biology; Economics; Economic growth; Physics","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":[0.0005372982,0.00046959,0.0002410914,0.001074416,0.0009067734,0.001043347,0.0008103951,0.000317841,0.004450432],"category_scores_gemma":[0.0005581346,0.0001845956,0.0003528339,0.001531266,0.0005631502,0.0004555477,0.001092325,0.0004285047,0.0002478524],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002382365,"about_ca_system_score_gemma":0.00248634,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0332968,"about_ca_topic_score_gemma":0.1111671,"domain_scores_codex":[0.9993315,0.0001718405,0.00002428523,0.00006454063,0.0002215807,0.0001862572],"domain_scores_gemma":[0.9994107,0.000156446,0.0001338798,0.00002986227,0.0001359998,0.0001329839],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008026125,0.002682998,0.6717249,0.003653531,0.0006868265,0.01784892,0.01216057,0.01034577,0.08155213,0.005307968,0.005568103,0.1876657],"study_design_scores_gemma":[0.00002662989,0.001874542,0.973032,0.0001686417,0.0001445219,0.0008976817,0.01089162,0.001281077,0.002045888,0.0004301685,0.00917744,0.00002973386],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9913477,0.0005098294,0.0001809505,0.0002450466,0.000009286157,0.0001117776,0.0003843164,0.00001565543,0.007195389],"genre_scores_gemma":[0.9963412,0.0007550885,0.0006156415,0.00007667713,0.000005343906,0.0000412748,0.0002830278,0.000004221435,0.001877612],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0332968,"threshold_uncertainty_score":0.06620598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06329825830130781,"score_gpt":0.3929014807563934,"score_spread":0.3296032224550856,"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."}}