{"id":"W4243971759","doi":"10.1109/iembs.2006.4397881","title":"Robust Contact Detection in Micromanipulation Using Computer Vision Microscopy","year":2006,"lang":"en","type":"article","venue":"Conference proceedings","topic":"Force Microscopy Techniques and Applications","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Microscopy; Computer vision; Computer science; Artificial intelligence; Optics; 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":[0.0004646863,0.0004484458,0.0005883356,0.0007628843,0.0003705272,0.0005625471,0.0008242237,0.001056772,0.0007225792],"category_scores_gemma":[0.001433133,0.000327476,0.0002976703,0.0003822868,0.0007433674,0.0008296675,0.000738501,0.0005564659,0.0002990906],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000566507,"about_ca_system_score_gemma":0.0004169974,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001064955,"about_ca_topic_score_gemma":0.0008679483,"domain_scores_codex":[0.9992959,0.00008954195,0.00002331202,0.0001410743,0.0003928358,0.00005724403],"domain_scores_gemma":[0.9995314,0.0002007634,0.00008276445,0.00005523832,0.0001067018,0.00002321659],"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":[0.0002224659,0.00009411205,0.0006658219,0.0002604928,0.00004041433,0.0002156164,0.0001528636,0.04790121,0.6690802,0.009647078,0.0009311234,0.2707886],"study_design_scores_gemma":[0.00004048531,0.0002893681,0.001963465,0.00002547135,0.0000210979,0.000552921,0.00002948609,0.7617437,0.2247005,0.005571234,0.004998479,0.00006383438],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02901622,0.0006213688,0.9687565,0.0000718298,0.00002823778,0.00003631055,0.00001049629,0.0007599208,0.0006990948],"genre_scores_gemma":[0.4549292,0.0005229588,0.5429983,0.0001028092,0.00004627091,0.00007920736,0.00004314313,0.0000779882,0.001200078],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001064955,"threshold_uncertainty_score":0.004110336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0217178617249051,"score_gpt":0.2769012639700615,"score_spread":0.2551834022451564,"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."}}