{"id":"W4242062912","doi":"10.24908/iqurcp.7878","title":"11. MEMS Seed Sorting Mechanism","year":2017,"lang":"en","type":"article","venue":"Inquiry Queen s Undergraduate Research Conference Proceedings","topic":"Magnetic and Electromagnetic Effects","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Sorting; Microelectromechanical systems; Dielectrophoresis; Process engineering; Computer science; Selection (genetic algorithm); Process (computing); Nanotechnology; Mechanical engineering; Biochemical engineering; Electronic engineering; Materials science; Engineering; Microfluidics; Artificial intelligence; Algorithm","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001900338,0.0003301523,0.0003085192,0.0001611263,0.001281598,0.0008937113,0.001336575,0.0003139183,0.000046793],"category_scores_gemma":[0.001552316,0.0003159435,0.0001133125,0.0001359052,0.0008804029,0.00004063729,0.0008963085,0.0005209974,0.0000831813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004692295,"about_ca_system_score_gemma":0.0003750685,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005496116,"about_ca_topic_score_gemma":0.00007443729,"domain_scores_codex":[0.9965438,0.00007554873,0.0003585054,0.0009202008,0.0008524619,0.001249436],"domain_scores_gemma":[0.9975252,0.0000445859,0.0002468052,0.0006872113,0.001128921,0.0003672629],"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":[0.0001332308,0.00007735822,0.002982397,0.0001157647,0.00006385211,0.0000148163,0.0003797481,3.532681e-7,0.9029522,0.08300778,0.00622657,0.004045939],"study_design_scores_gemma":[0.002342738,0.003576962,0.009138969,0.0002690913,0.00005817754,0.00009408005,0.001524619,0.001185756,0.7833261,0.1759299,0.02127309,0.001280496],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9621391,0.0001057566,0.001984938,0.01201225,0.0002503666,0.000727377,0.000004050823,0.00006822575,0.02270788],"genre_scores_gemma":[0.9904453,0.000545762,0.0006773529,0.0001160394,0.0006517327,0.0001526638,0.0000235528,0.00005607471,0.007331483],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.119626,"threshold_uncertainty_score":0.9999292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0589658671080769,"score_gpt":0.3598227264953942,"score_spread":0.3008568593873173,"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."}}