{"id":"W2002965655","doi":"10.1117/12.443076","title":"<title>Self-assembly of surface-micromachined structures using electrostatic attraction</title>","year":2001,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Semiconductor Lasers and Optical Devices","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Surface micromachining; Lift (data mining); Voltage; Process (computing); Electrostatics; Optoelectronics; Materials science; Surface (topology); Electrical engineering; Computer science; Engineering; Fabrication; Physics","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":[0.0001799593,0.0002175063,0.0001853017,0.0002511796,0.000381407,0.0005409082,0.0004449651,0.0002790515,0.01358478],"category_scores_gemma":[0.0002036775,0.0001628912,0.0002220356,0.0002016697,0.0003553327,0.0005318933,0.0002627351,0.0003948876,0.004631595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002619053,"about_ca_system_score_gemma":0.0001504669,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002481071,"about_ca_topic_score_gemma":0.0005398037,"domain_scores_codex":[0.9998723,0.0000115787,0.000008066163,0.00002656106,0.0000626577,0.00001869139],"domain_scores_gemma":[0.999889,0.00002318659,0.00001617433,0.00001942322,0.00003907899,0.00001308328],"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":[0.0001703709,0.00009466911,0.0004354352,0.000355132,0.00002499014,0.0009053809,0.0001805866,0.001920907,0.8014538,0.02461705,0.03649063,0.1333511],"study_design_scores_gemma":[0.00002674241,0.0002220876,0.000953757,0.0000186679,0.00001555474,0.0004328819,0.00004682468,0.00949078,0.8375729,0.002041118,0.1491496,0.00002900742],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.390404,0.0111288,0.277101,0.00631734,0.01859803,0.0004108028,0.000778729,0.007073237,0.2881881],"genre_scores_gemma":[0.5681556,0.003514341,0.05464611,0.0008294147,0.001256635,0.00009222039,0.0008164599,0.0009320799,0.3697571],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01358478,"threshold_uncertainty_score":0.04544556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01091286352037766,"score_gpt":0.2307063093451223,"score_spread":0.2197934458247446,"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."}}