{"id":"W27314943","doi":"10.1016/j.infbeh.2016.05.003","title":"Higher Yields by Means of an Optimised Mash Preparation","year":2000,"lang":"en","type":"article","venue":"Fruit processing","topic":"Autism Spectrum Disorder Research","field":"Neuroscience","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Eunice Kennedy Shriver National Institute of Child Health and Human Development","keywords":"Food science; Mathematics; Chemistry","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":[0.001315427,0.0009049523,0.0008988223,0.001100509,0.0008091095,0.0009806472,0.001105224,0.0008797559,0.0179269],"category_scores_gemma":[0.002401157,0.0006270368,0.0005885987,0.00103525,0.0005546269,0.001629109,0.001774036,0.001788688,0.01088985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004746418,"about_ca_system_score_gemma":0.0007099836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005984897,"about_ca_topic_score_gemma":0.00139175,"domain_scores_codex":[0.999167,0.00008837163,0.00005328503,0.0002706496,0.000208811,0.0002119761],"domain_scores_gemma":[0.9991409,0.0001799697,0.0001422236,0.0002145546,0.0001966746,0.0001256898],"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":[0.0007365874,0.0001607242,0.002003008,0.0002973552,0.00005047963,0.0002934266,0.0002023932,0.00190531,0.9246507,0.00378163,0.002505329,0.06341301],"study_design_scores_gemma":[0.0001141452,0.001488316,0.004839187,0.00006145892,0.00007100454,0.0004248461,0.0001771071,0.009132174,0.9339747,0.002560956,0.04706074,0.00009536625],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5593655,0.003395604,0.3880813,0.001476519,0.001233409,0.001219388,0.001913584,0.006464651,0.03685008],"genre_scores_gemma":[0.7210231,0.002409932,0.2266548,0.0006285441,0.0003812916,0.001152488,0.002154069,0.002368063,0.04322765],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0179269,"threshold_uncertainty_score":0.05997145,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03692263577247049,"score_gpt":0.3275770149901773,"score_spread":0.2906543792177068,"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."}}