{"id":"W2789980209","doi":"10.1007/s10404-018-2048-2","title":"Desktop micromilled microfluidics","year":2018,"lang":"en","type":"article","venue":"Microfluidics and Nanofluidics","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":55,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"McGill University; National Science Foundation","keywords":"Microfluidics; Rapid prototyping; Software; Computer science; Substrate (aquarium); Overhead (engineering); Stack (abstract data type); Nanotechnology; Mechanical engineering; Embedded system; Materials science; Engineering; Operating system","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005203208,0.0007345179,0.0005221641,0.001005214,0.0006119696,0.001318601,0.001507973,0.0007873905,0.05066934],"category_scores_gemma":[0.0009817212,0.0006323692,0.0003861139,0.0005210382,0.0003759785,0.001415777,0.001531535,0.0009065035,0.01204943],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009416106,"about_ca_system_score_gemma":0.001515579,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001452298,"about_ca_topic_score_gemma":0.00217579,"domain_scores_codex":[0.998875,0.00004627808,0.00007709664,0.0003110992,0.0005823218,0.0001083667],"domain_scores_gemma":[0.9994901,0.0001239629,0.00007287807,0.0001169481,0.0001223761,0.00007366952],"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":[0.0002314289,0.0001567621,0.0005672814,0.0004459484,0.00003132176,0.0001523103,0.0001446387,0.0008029571,0.7865434,0.01305507,0.03140176,0.1664672],"study_design_scores_gemma":[0.00009143937,0.0002829513,0.001177687,0.00004216805,0.00003494347,0.0005372924,0.00003845153,0.01038615,0.6104331,0.002262027,0.3746193,0.00009453453],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1346774,0.01075593,0.5068395,0.003372044,0.003755347,0.001537502,0.01739871,0.06407665,0.2575869],"genre_scores_gemma":[0.3253231,0.004637181,0.4328322,0.001988475,0.001009494,0.001354379,0.009719338,0.0020777,0.2210581],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05066934,"threshold_uncertainty_score":0.1695058,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0082637215971147,"score_gpt":0.2134009123478645,"score_spread":0.2051371907507498,"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."}}