{"id":"W2398829434","doi":"","title":"A challenger appears: a copper nanocolloid for MR detection of atherosclerotic plaques.","year":2011,"lang":"en","type":"article","venue":"PubMed","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University Health Network; Ontario Institute for Cancer Research","funders":"","keywords":"Copper; Materials science; Metallurgy; Chemistry; Biomedical engineering; Medicine","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":[0.0006770848,0.0006674814,0.0004611241,0.0004692739,0.0007164406,0.001046365,0.0008989499,0.002704494,0.008490837],"category_scores_gemma":[0.000966915,0.0002969894,0.0002872682,0.0002061343,0.0005553129,0.001502605,0.0008500492,0.001144411,0.003570553],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005287898,"about_ca_system_score_gemma":0.0004926961,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005300809,"about_ca_topic_score_gemma":0.0007747392,"domain_scores_codex":[0.9996473,0.00007946096,0.00001835811,0.00009870854,0.0001142244,0.0000419131],"domain_scores_gemma":[0.9997285,0.00007371661,0.0000201568,0.00003049046,0.00006092601,0.00008629003],"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":[0.00238546,0.0003321749,0.0007889909,0.001250591,0.0000618663,0.005227242,0.0004247426,0.000238063,0.7724974,0.006694588,0.05861443,0.1514844],"study_design_scores_gemma":[0.0004630116,0.002835609,0.001491588,0.0001523094,0.0001330357,0.0109217,0.0003521427,0.002294603,0.7356843,0.002628241,0.2429208,0.0001227806],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5067031,0.09286197,0.1578155,0.07955071,0.02841403,0.002567583,0.001586118,0.004440712,0.1260603],"genre_scores_gemma":[0.6369265,0.02343203,0.09960274,0.02040697,0.003748288,0.0005470346,0.001625861,0.0007895837,0.212921],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008490837,"threshold_uncertainty_score":0.02840465,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03280465845784801,"score_gpt":0.1812030952148482,"score_spread":0.1483984367570002,"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."}}