{"id":"W2507932840","doi":"10.1371/journal.pone.0161991","title":"Multi-Modal Imaging in a Mouse Model of Orthotopic Lung Cancer","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Nanoplatforms for cancer theranostics","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Toronto General Hospital; University Health Network","funders":"Canadian Cancer Society Research Institute; Princess Margaret Cancer Foundation","keywords":"Lung cancer; Medicine; Nuclear medicine; Indocyanine green; Hounsfield scale; Fluorescence-lifetime imaging microscopy; Iohexol; Ex vivo; Pathology; Lung; In vivo; Positron emission tomography; Fluorescence; Radiology; Computed tomography; Biology; Internal medicine","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":[0.0005788477,0.0007142265,0.0003865591,0.0008773667,0.000161129,0.0002457766,0.000332959,0.0006260521,0.001101401],"category_scores_gemma":[0.0001004649,0.0002521572,0.0003863915,0.0002785284,0.000294748,0.0004272519,0.0002028206,0.0008881176,0.0003758606],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003787377,"about_ca_system_score_gemma":0.000235436,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007557167,"about_ca_topic_score_gemma":0.001104711,"domain_scores_codex":[0.999752,0.00003163501,0.00001518036,0.00007483975,0.00007377446,0.00005262076],"domain_scores_gemma":[0.9998263,0.00002407119,0.00005857803,0.00002473143,0.00002613012,0.00004032511],"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":[0.0002397751,0.0001451971,0.0001361468,0.00003580283,0.000005223293,0.00003389094,0.00001239098,0.0001339223,0.9980959,0.00004013228,0.00004433562,0.001077326],"study_design_scores_gemma":[0.00005771035,0.0029267,0.004772237,0.00001092085,0.00004227852,0.0005187404,0.00002641164,0.002923686,0.9866325,0.00006296617,0.00201466,0.00001118227],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9795242,0.002709038,0.01413269,0.0001922732,0.00005310102,0.0002184831,0.0009168359,0.0004196942,0.001833573],"genre_scores_gemma":[0.97557,0.001771248,0.0162539,0.0001471767,0.00002787842,0.0003591492,0.001098143,0.00007885184,0.004693682],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001101401,"threshold_uncertainty_score":0.00368458,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02802442985113705,"score_gpt":0.2272704590964664,"score_spread":0.1992460292453294,"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."}}