{"id":"W4395689830","doi":"10.1016/j.heliyon.2024.e30397","title":"Impact of positive selection technology on seed yam productivity","year":2024,"lang":"en","type":"article","venue":"Heliyon","topic":"Agricultural risk and resilience","field":"Agricultural and Biological Sciences","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Menzies School of Health Research; Bill and Melinda Gates Foundation; Ministry of Agriculture and Food","keywords":"Productivity; Cropping; Agricultural science; Propensity score matching; Matching (statistics); Business; Selection (genetic algorithm); Agricultural economics; Marketing; Biotechnology; Economics; Agriculture; Mathematics; Geography; Biology; Economic growth; Statistics; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0000618366,0.00009345218,0.0001035851,0.00002290841,0.00007909427,0.00001945514,0.00008447059,0.00009375389,0.00006088159],"category_scores_gemma":[0.00003177314,0.00002461752,0.00008925109,0.0008065632,0.00005278094,0.00008378847,0.00002302542,0.0001182648,0.00004808367],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004846901,"about_ca_system_score_gemma":0.000009055041,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008782637,"about_ca_topic_score_gemma":0.0001039729,"domain_scores_codex":[0.999366,0.00002805684,0.00009125938,0.0002428515,0.0001147095,0.0001570653],"domain_scores_gemma":[0.9997975,0.00005402401,0.00002998431,0.00002546815,0.00006192821,0.00003113835],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00003122682,0.0000744576,0.02938322,0.00001658224,0.00001555263,0.000002764936,0.00003631405,0.00003316054,0.9079046,0.0003355238,0.0001141661,0.06205245],"study_design_scores_gemma":[0.00002136684,0.001097506,0.8855352,0.0001292196,0.000006829552,0.00002024281,0.00004426073,0.00002717571,0.1123917,0.0001491254,0.0004927157,0.00008460714],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9974285,0.0006795618,0.00000218025,0.0008943895,0.00009283287,0.0001489368,0.00001836799,0.0001312429,0.0006039268],"genre_scores_gemma":[0.9990609,0.000182418,0.00001249408,0.00000719014,0.0001632905,0.000006435056,0.000009005531,4.685351e-7,0.0005578222],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8561521,"threshold_uncertainty_score":0.1003873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0074435617337703,"score_gpt":0.2440967387897427,"score_spread":0.2366531770559724,"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."}}