{"id":"W2800488438","doi":"10.3390/mi9050215","title":"CO2 Laser-Based Rapid Prototyping of Micropumps","year":2018,"lang":"en","type":"article","venue":"Micromachines","topic":"Microfluidic and Capillary Electrophoresis Applications","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cleanroom; Fabrication; Rapid prototyping; Microfluidics; Fluidics; Process (computing); Peristaltic pump; Laser; Mechanical engineering; Materials science; Computer science; Engineering; Nanotechnology; Electrical engineering; Optics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00007767416,0.0001484492,0.000172804,0.00008479365,0.00007937077,0.00001266806,0.0001867205,0.00006238911,0.0003397393],"category_scores_gemma":[0.000006489346,0.0001394179,0.0000670588,0.0002549306,0.0001110555,0.00003122369,0.00001616319,0.00008101347,0.00009495066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002188026,"about_ca_system_score_gemma":0.00002401318,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002276901,"about_ca_topic_score_gemma":0.000006594438,"domain_scores_codex":[0.9993199,0.00001809194,0.0002303931,0.0001511966,0.00006926715,0.0002112278],"domain_scores_gemma":[0.9995471,0.00002020596,0.00003560789,0.0002872717,0.00006506869,0.00004480486],"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":[0.00001333058,0.00002727417,0.0002407205,0.00007042314,0.00002472286,5.530482e-7,0.00006207822,0.000004075212,0.9636726,0.00007414413,0.03155866,0.004251463],"study_design_scores_gemma":[0.0002052119,0.0000562363,0.0007698204,0.00002131351,0.00001231319,0.000004773903,0.000005716213,0.0005807698,0.7953714,0.00005904759,0.2027883,0.0001250932],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748964,0.02055206,0.001704928,0.00007082203,0.00008383876,0.0003639519,0.00003210855,0.0002125653,0.002083335],"genre_scores_gemma":[0.9960235,0.00277017,0.0007262324,0.00009345426,0.0001618626,0.00006672885,0.00003257458,0.00004445272,0.00008101985],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1712297,"threshold_uncertainty_score":0.5685296,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006455217465408222,"score_gpt":0.209490358096026,"score_spread":0.2030351406306177,"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."}}