{"id":"W4408289021","doi":"10.2139/ssrn.5170736","title":"Nano sensors for Plant Science Insights and Applications for the Agriculture Productivity","year":2025,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Gas Sensing Nanomaterials and Sensors","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Productivity; Nano-; Agriculture; Agricultural engineering; Agricultural economics; Environmental science; Engineering; Computer science; Economics; Geography; Economic growth; Archaeology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004610586,0.0006515473,0.0005544738,0.0008612617,0.0002943251,0.001599685,0.0005559386,0.001836857,0.009491019],"category_scores_gemma":[0.0005011167,0.0003425231,0.0004138418,0.0007146135,0.0006998736,0.001853171,0.0007775805,0.00155316,0.002826191],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009485043,"about_ca_system_score_gemma":0.0004965916,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000440027,"about_ca_topic_score_gemma":0.0009931485,"domain_scores_codex":[0.999734,0.00004219926,0.00001134265,0.0000710048,0.0001210272,0.0000204124],"domain_scores_gemma":[0.9997056,0.0001241352,0.00004275848,0.00002206848,0.00007972824,0.00002560463],"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":[0.0001859341,0.00009382771,0.001112413,0.001128713,0.0000535597,0.0001824112,0.0001019379,0.001305174,0.7942638,0.04527296,0.01245903,0.1438401],"study_design_scores_gemma":[0.00002755346,0.0003183212,0.002684581,0.0002299971,0.00008729532,0.000417783,0.0004386423,0.01044394,0.6429135,0.04352985,0.298842,0.00006656727],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.1206385,0.3501825,0.3186923,0.04666891,0.01094741,0.0001905848,0.003764865,0.003127451,0.1457874],"genre_scores_gemma":[0.647296,0.1308346,0.139882,0.006449309,0.002475676,0.0001534387,0.0009906805,0.0004400046,0.07147841],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.009491019,"threshold_uncertainty_score":0.03175062,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004538806637742189,"score_gpt":0.2025185072725582,"score_spread":0.197979700634816,"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."}}