{"id":"W1522568210","doi":"10.1126/science.1165719","title":"Putting Electrowetting to Work","year":2008,"lang":"en","type":"article","venue":"Science","topic":"Electrowetting and Microfluidic Technologies","field":"Engineering","cited_by":311,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Electrowetting; Work (physics); Computer science; Computer graphics (images); Engineering; Mechanical engineering; Electrical engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007990146,0.001164379,0.0009093583,0.0009122576,0.0009952376,0.003498766,0.00153563,0.002045315,0.007678029],"category_scores_gemma":[0.003684991,0.0008889481,0.0008147516,0.000724035,0.002402622,0.005463789,0.002110457,0.005163399,0.006177417],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004738773,"about_ca_system_score_gemma":0.0006541518,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004469205,"about_ca_topic_score_gemma":0.0005558305,"domain_scores_codex":[0.998705,0.0001164703,0.00009552219,0.0002439091,0.000667405,0.0001716608],"domain_scores_gemma":[0.9985293,0.0003830803,0.0001168488,0.000444723,0.0003552685,0.0001705971],"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":[0.0001321618,0.0001398786,0.00054481,0.0007517438,0.00009988678,0.0005356279,0.0005279636,0.0009153901,0.8487961,0.03703122,0.01169905,0.09882624],"study_design_scores_gemma":[0.00007257824,0.0004089781,0.0006355412,0.000214274,0.00009560642,0.0005219746,0.00037054,0.001898541,0.7542124,0.03016518,0.2112784,0.000125933],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2516183,0.02923637,0.4646606,0.04195438,0.05689545,0.0006768457,0.0007267452,0.01181358,0.1424178],"genre_scores_gemma":[0.5798393,0.02997467,0.2508553,0.02234186,0.004645839,0.0006891535,0.0009583053,0.003160373,0.1075353],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007678029,"threshold_uncertainty_score":0.02568555,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007534951979662665,"score_gpt":0.1920656441259501,"score_spread":0.1845306921462875,"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."}}