{"id":"W2263502697","doi":"10.1007/978-3-540-39903-2_30","title":"Laser Projection Augmented Reality System for Computer Assisted Surgery","year":2003,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Augmented Reality Applications","field":"Computer Science","cited_by":39,"is_retracted":false,"has_abstract":false,"ca_institutions":"Robarts Clinical Trials; Western University","funders":"Georgetown University","keywords":"Computer science; Projection (relational algebra); Computer vision; Artificial intelligence; Augmented reality; Fiducial marker; Visualization; Computer graphics (images); Craniotomy; Algorithm; Surgery","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":[0.000447715,0.0007842541,0.0007635505,0.0008833623,0.0003787208,0.001275193,0.001525797,0.001505955,0.03302733],"category_scores_gemma":[0.0006890571,0.0008730602,0.0008410689,0.0007447592,0.0002390025,0.00103776,0.001231623,0.001098646,0.01093023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001883418,"about_ca_system_score_gemma":0.0005882661,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001086392,"about_ca_topic_score_gemma":0.001492827,"domain_scores_codex":[0.9994038,0.0001042938,0.00003312895,0.00007638062,0.0003497345,0.00003253128],"domain_scores_gemma":[0.9996363,0.00009825982,0.00001575704,0.00009936206,0.0001255677,0.00002474702],"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":[0.0007108841,0.0001289334,0.000548955,0.0004204492,0.00009920511,0.0005577651,0.0003309923,0.004908121,0.1455277,0.006242775,0.04407557,0.7964487],"study_design_scores_gemma":[0.0003900177,0.002153904,0.01039987,0.0004580882,0.0008026552,0.01719743,0.0003157683,0.2399703,0.2898906,0.008006775,0.429736,0.000678635],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.009716504,0.001748588,0.9603571,0.0002392806,0.000374141,0.0001807091,0.0009356978,0.0130766,0.01337141],"genre_scores_gemma":[0.1417239,0.004349459,0.7892813,0.0006337115,0.0002987205,0.0005710656,0.002587475,0.001426499,0.05912792],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03302733,"threshold_uncertainty_score":0.1104874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04275643666646558,"score_gpt":0.2743335498648735,"score_spread":0.2315771131984079,"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."}}