{"id":"W2017535287","doi":"10.1364/oe.15.011154","title":"Magnetically actuated MEMS microlens scanner for in vivo medical imaging†","year":2007,"lang":"en","type":"article","venue":"Optics Express","topic":"Optical Coherence Tomography Applications","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; CMC Microsystems","keywords":"Scanner; Materials science; Microlens; Optics; Microelectromechanical systems; Polydimethylsiloxane; Magnetic field; Optoelectronics; Lens (geology); Physics; Nanotechnology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001164899,0.000203192,0.0001552561,0.0001605758,0.0001638066,0.0001482074,0.0002729386,0.0003404782,0.001264862],"category_scores_gemma":[0.000162635,0.0001649411,0.0000895749,0.00007926213,0.0001559624,0.0001977676,0.0001800426,0.0002080007,0.0003957573],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001900047,"about_ca_system_score_gemma":0.0001886283,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002426519,"about_ca_topic_score_gemma":0.000742923,"domain_scores_codex":[0.9999228,0.000008733793,0.000003404413,0.00001278302,0.00004321445,0.000009055209],"domain_scores_gemma":[0.9999126,0.00003211083,0.00001972624,0.000005570764,0.00001763475,0.00001235841],"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":[0.0000274216,0.000005519023,0.00008019259,0.00003168796,0.00000274337,0.00005792771,0.000009158312,0.0001025254,0.9931311,0.0002596159,0.0002155607,0.006076605],"study_design_scores_gemma":[0.00002544903,0.0001929366,0.002380293,0.000006800436,0.00001400343,0.0008983137,0.00001581091,0.01019618,0.9749287,0.0002263588,0.01109233,0.00002295679],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7920119,0.007738803,0.1856751,0.001290919,0.0006435246,0.0002262113,0.0007823572,0.001698853,0.009932281],"genre_scores_gemma":[0.8019654,0.001356076,0.1889617,0.0003844359,0.0001682031,0.00009944884,0.0002681122,0.00004940481,0.006747212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001264862,"threshold_uncertainty_score":0.004231393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007152934812950053,"score_gpt":0.2435520147064762,"score_spread":0.2363990798935262,"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."}}