{"id":"W2008730299","doi":"10.1109/tim.2013.2277538","title":"Instrument for Haptic Image Exploration","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Instrumentation and Measurement","topic":"Advanced Vision and Imaging","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Haptic technology; Computer vision; Computer science; Artificial intelligence; Zoom; Rendering (computer graphics); Computer graphics (images); Image segmentation; Image texture; Image (mathematics)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0007635182,0.000750458,0.0006641206,0.0006014087,0.0004219062,0.000973632,0.001659756,0.001189383,0.01836267],"category_scores_gemma":[0.004614395,0.0004293293,0.0006153167,0.0003866566,0.0007486095,0.002119507,0.002893352,0.0008489661,0.002311333],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00020192,"about_ca_system_score_gemma":0.0002270581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001791152,"about_ca_topic_score_gemma":0.0001360686,"domain_scores_codex":[0.9993344,0.00009904997,0.00004156749,0.0001017962,0.000325307,0.00009785876],"domain_scores_gemma":[0.997747,0.001243384,0.00010358,0.0004991076,0.000233065,0.0001738108],"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":[0.002321042,0.0004447138,0.001636918,0.0009988267,0.00007388277,0.0009720181,0.001332906,0.004187437,0.6176382,0.01466059,0.01207106,0.3436624],"study_design_scores_gemma":[0.001161705,0.007138219,0.01539862,0.0006337218,0.0003515088,0.008234712,0.001014254,0.1715346,0.4850574,0.01361831,0.295113,0.0007440198],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1252487,0.00122247,0.837278,0.0006515185,0.0004601747,0.000892628,0.0008431303,0.01726497,0.01613842],"genre_scores_gemma":[0.5518782,0.0006504615,0.4289426,0.0006836113,0.0002064129,0.001134592,0.0005726717,0.0009296386,0.01500175],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01836267,"threshold_uncertainty_score":0.06142926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06032936411708986,"score_gpt":0.2797690009970009,"score_spread":0.219439636879911,"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."}}