{"id":"W2648662755","doi":"10.1109/ccece.2017.7946805","title":"Manifold 2.0: A hardware description language for microfluidic devices","year":2017,"lang":"en","type":"article","venue":"","topic":"Modeling and Simulation Systems","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Programming language; Domain-specific language; Microfluidics; Domain (mathematical analysis); Computer architecture; Hardware description language; USable; Variety (cybernetics); Class (philosophy); Syntax; Computer hardware; Artificial intelligence; Field-programmable gate array","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002464188,0.0000635819,0.00008560096,0.00003574921,0.0003526868,0.0006588521,0.000634548,0.00003638634,0.000008999366],"category_scores_gemma":[0.00002889859,0.00005250901,0.0000501754,0.00001814955,0.000006048724,0.0005191295,0.00007631847,0.00002379624,0.00006117391],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001417823,"about_ca_system_score_gemma":0.00001635483,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001939243,"about_ca_topic_score_gemma":0.00003670511,"domain_scores_codex":[0.9994218,0.00001417402,0.000129347,0.0002053962,0.0001026711,0.0001266193],"domain_scores_gemma":[0.9991459,0.00001865803,0.00008355844,0.0006371869,0.00007350528,0.00004118862],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004993667,0.0001918047,0.04103274,0.0005163527,0.000146035,0.00003761298,0.01518387,0.000490056,0.09692924,0.5676866,0.1181242,0.1596116],"study_design_scores_gemma":[0.0009235136,0.0000569576,0.006693899,0.00007097719,0.000009153881,0.00001270574,0.0002505479,0.910812,0.01009172,0.00113949,0.06961124,0.0003277916],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04622609,0.0003083715,0.9494186,0.0003907109,0.0003618174,0.0001559057,0.000002461103,0.0001358074,0.003000232],"genre_scores_gemma":[0.9719134,0.000004043526,0.02235596,0.0002116095,0.0001029066,0.00001650011,0.000002643366,0.000004763045,0.005388152],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9270626,"threshold_uncertainty_score":0.6353326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06189310963669527,"score_gpt":0.3055453899774084,"score_spread":0.2436522803407132,"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."}}