{"id":"W2094627020","doi":"10.1109/tro.2014.2298551","title":"Robotic Probing of Nanostructures inside Scanning Electron Microscopy","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Robotics","topic":"Integrated Circuits and Semiconductor Failure Analysis","field":"Engineering","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Metrology; Scanning electron microscope; Visual servoing; Materials science; Chip; Rendering (computer graphics); Computer science; Noise (video); Artificial intelligence; Computer vision; Electronic engineering; Robot; Optics; Engineering; Physics; Image (mathematics)","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":[0.0002117608,0.0002325602,0.0002095076,0.0001997232,0.0002539987,0.000254139,0.0004205003,0.0003547044,0.0007450634],"category_scores_gemma":[0.000403601,0.0001777939,0.0001605157,0.00008660958,0.0003417165,0.0003292629,0.0004307525,0.0002537929,0.0002871447],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002054311,"about_ca_system_score_gemma":0.0001809337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004503452,"about_ca_topic_score_gemma":0.0007505871,"domain_scores_codex":[0.9997777,0.00002793332,0.000009702469,0.00005427946,0.000111094,0.0000193725],"domain_scores_gemma":[0.999727,0.0001023467,0.00004050054,0.0000807335,0.00003671397,0.00001277705],"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":[0.00002970907,0.00001361408,0.0002311981,0.00004079092,0.000004057139,0.00004644996,0.00004288211,0.001282264,0.9858727,0.0008957739,0.0001709901,0.01136944],"study_design_scores_gemma":[0.00001780464,0.0002610391,0.00269359,0.00001238614,0.00001221582,0.0004276252,0.00003520745,0.03639545,0.9491739,0.0008751143,0.01006749,0.00002825536],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6295624,0.0007772733,0.3588933,0.0001803115,0.0001047523,0.0001903189,0.000153676,0.001751447,0.00838661],"genre_scores_gemma":[0.7887223,0.0003265476,0.2075837,0.00008758829,0.00002770762,0.0001140647,0.00009077668,0.00005246691,0.002994842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007450634,"threshold_uncertainty_score":0.002492487,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008243030797639309,"score_gpt":0.2218560179409434,"score_spread":0.2136129871433041,"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."}}