{"id":"W174392811","doi":"10.1007/978-3-319-10470-6_43","title":"Enhanced Differential Evolution to Combine Optical Mouse Sensor with Image Structural Patches for Robust Endoscopic Navigation","year":2014,"lang":"en","type":"article","venue":"Lecture notes in computer science","topic":"Advanced Image and Video Retrieval Techniques","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Japan Society for the Promotion of Science","keywords":"Computer vision; Computer science; Artificial intelligence; Endoscope; Tracking (education); Distortion (music); Navigation system; Imaging phantom; Physics; Optics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000308997,0.0002554033,0.0002756148,0.0002305133,0.0002546136,0.0003746791,0.001076537,0.00007266767,0.000001653921],"category_scores_gemma":[0.000246904,0.0001982154,0.00004679001,0.001087935,0.0002828815,0.0009994484,0.0003495955,0.0002142421,0.000003812397],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00017555,"about_ca_system_score_gemma":0.00008841195,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001710155,"about_ca_topic_score_gemma":0.00001615742,"domain_scores_codex":[0.9977556,0.00005152421,0.0002752906,0.0008726736,0.0004748476,0.0005700883],"domain_scores_gemma":[0.998486,0.0003322981,0.0000987841,0.0006234192,0.0003020676,0.0001574737],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00007557355,0.00006465547,0.0004327793,0.0000548149,0.000005673342,0.000004890462,0.0006332915,0.02602138,0.4676988,0.003183678,0.000004529828,0.5018199],"study_design_scores_gemma":[0.0004164546,0.0005829413,0.001599623,0.00005846158,0.000002597564,0.00000814548,5.542547e-7,0.4278274,0.5633815,0.005922772,0.000003830125,0.0001957867],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2301758,0.000006593523,0.7686314,0.000371305,0.0002466264,0.0003791225,0.000001987892,0.000183045,0.000004075576],"genre_scores_gemma":[0.5096573,4.056866e-7,0.4900713,0.0001500294,0.00008972731,0.00002028587,0.000002530095,0.000006953369,0.00000146133],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.5016242,"threshold_uncertainty_score":0.8082991,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009438246532576742,"score_gpt":0.2623319592506772,"score_spread":0.2528937127181005,"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."}}