{"id":"W2890215119","doi":"10.1002/jbio.201800153","title":"Optimizing interstitial photodynamic therapy with custom cylindrical diffusers","year":2018,"lang":"en","type":"article","venue":"Journal of Biophotonics","topic":"Photoacoustic and Ultrasonic Imaging","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Princess Margaret Cancer Centre; University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Ontario Centres of Excellence; International Business Machines Corporation","keywords":"Photodynamic therapy; Diffuser (optics); Materials science; Wavelength; Computer science; Biomedical engineering; Optics; Optoelectronics; Nanotechnology; Chemistry; Physics; Light source; 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":[0.000235043,0.0005304079,0.0002083429,0.0001564748,0.00008383176,0.0004242173,0.0002787088,0.0002524629,0.0005743814],"category_scores_gemma":[0.0004794569,0.0002098539,0.0002670825,0.0001907344,0.0001931922,0.0003263906,0.0003062793,0.0002007408,0.0001734945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004150028,"about_ca_system_score_gemma":0.0003296992,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006758455,"about_ca_topic_score_gemma":0.001287342,"domain_scores_codex":[0.9998716,0.00002599822,0.000008304358,0.00002571264,0.00005025828,0.00001802188],"domain_scores_gemma":[0.9998558,0.00004267759,0.00005206432,0.00001688551,0.00002353146,0.000009068776],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001391617,0.00005840826,0.0007326443,0.000144718,0.0000186731,0.00009512448,0.00004957967,0.5914413,0.3710111,0.002369723,0.0003534337,0.03358605],"study_design_scores_gemma":[0.00004047063,0.0003882519,0.001431955,0.00001277824,0.00002802541,0.0002448001,0.00004916534,0.843437,0.1494294,0.0007984266,0.004101989,0.00003766479],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2694012,0.0007890988,0.7238421,0.0001126274,0.00002700634,0.0001033714,0.0001141079,0.0006829602,0.004927512],"genre_scores_gemma":[0.8229376,0.0004361816,0.1747238,0.0000264428,0.000005261721,0.0000589198,0.00007073829,0.0001245207,0.001616542],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0006758455,"threshold_uncertainty_score":0.003011048,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006692653860555923,"score_gpt":0.213742681812528,"score_spread":0.2070500279519721,"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."}}