{"id":"W4249694557","doi":"10.22215/etd/2012-06727","title":"Multi-spectral imaging system calibration and data fusion for applications in the assessment of rheumatoid Arthritis","year":2012,"lang":"en","type":"dissertation","venue":"","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University; Canadian Heritage; Library and Archives Canada","funders":"","keywords":"Rheumatoid arthritis; Calibration; Sensor fusion; Computer science; Artificial intelligence; Mathematics; Medicine; Statistics","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":[0.001645799,0.0004470486,0.0004890544,0.001439118,0.000368716,0.0009433392,0.0005013365,0.001148305,0.002870544],"category_scores_gemma":[0.003157255,0.0003396819,0.000674815,0.0008256941,0.0002691346,0.0008327155,0.0007016232,0.0006156015,0.001113555],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003825552,"about_ca_system_score_gemma":0.000824556,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001533967,"about_ca_topic_score_gemma":0.002579281,"domain_scores_codex":[0.9992108,0.0002164931,0.00004454662,0.0001218741,0.0003419124,0.00006441036],"domain_scores_gemma":[0.9992223,0.0002448383,0.00006860064,0.00008695461,0.000340868,0.00003641817],"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":[0.0008752189,0.0003302618,0.008313823,0.0004376692,0.0001482182,0.000132768,0.0002041384,0.02390823,0.2355428,0.001828127,0.005338957,0.7229398],"study_design_scores_gemma":[0.00007714879,0.0006356853,0.05323357,0.000177656,0.0002936167,0.00103774,0.00029249,0.6336823,0.2852164,0.004329362,0.02088914,0.0001349041],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1226915,0.006822113,0.860269,0.001221735,0.0003893879,0.0002193934,0.0005057542,0.00214685,0.005734204],"genre_scores_gemma":[0.5362824,0.00304315,0.4548608,0.0002943326,0.0001543194,0.0001930936,0.0006703526,0.0001743931,0.004327179],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002870544,"threshold_uncertainty_score":0.009602904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02523411180573736,"score_gpt":0.3228354054214402,"score_spread":0.2976012936157028,"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."}}