{"id":"W4403609830","doi":"10.53555/sfs.v10i3.3106","title":"Enhancing Crops Sustainably Through The Combined Use Of Microbiological And Silicon Resources","year":2023,"lang":"en","type":"article","venue":"Journal of Survey in Fisheries Sciences","topic":"Magnetic and Electromagnetic Effects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"University Grants Commission; Council of Scientific and Industrial Research, India","keywords":"Sustainability; Silicon; Business; Environmental science; Agroforestry; Natural resource economics; Agricultural engineering; Engineering; Materials science; Economics; Ecology; Biology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002216196,0.000365486,0.0002814055,0.0004303273,0.0002552015,0.0005353903,0.000254762,0.0003996474,0.001474899],"category_scores_gemma":[0.0001733141,0.0001015903,0.0003615078,0.0003543301,0.0002580404,0.0005059962,0.0005273573,0.0003606753,0.0003691558],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003454422,"about_ca_system_score_gemma":0.00059355,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005495975,"about_ca_topic_score_gemma":0.00243472,"domain_scores_codex":[0.9998885,0.0000194676,0.000008468209,0.000020733,0.00004152902,0.00002136282],"domain_scores_gemma":[0.9999201,0.00001758941,0.00002156537,0.000004897398,0.00002401289,0.00001189288],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00009425249,0.0000695932,0.002264168,0.002885866,0.0001026079,0.0003507225,0.0001080383,0.0009339374,0.8563835,0.002802466,0.0009522433,0.1330526],"study_design_scores_gemma":[0.00005226928,0.001665669,0.02546917,0.0009353356,0.0006107521,0.001739408,0.00101811,0.00269051,0.6431698,0.007973584,0.3146034,0.00007200095],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6286507,0.2718783,0.03807284,0.004849947,0.0007665598,0.000125305,0.0008104948,0.0003857488,0.05445997],"genre_scores_gemma":[0.8635291,0.1081485,0.01870988,0.0006119417,0.000187496,0.00005963377,0.0002895751,0.00003583338,0.008428185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001474899,"threshold_uncertainty_score":0.004934013,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06467916012669794,"score_gpt":0.2631536292646612,"score_spread":0.1984744691379633,"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."}}