{"id":"W4402980668","doi":"10.26685/urncst.673","title":"Exploring the Potential of Antisense Technologies to Enhance Traditional Antifungal Treatments for Candida albicans Biofilms","year":2024,"lang":"en","type":"article","venue":"Undergraduate Research in Natural and Clinical Science and Technology (URNCST) Journal","topic":"Advanced Chemical Sensor Technologies","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Queen's University; McGill University Health Centre; University of Calgary","funders":"","keywords":"Biofilm; Candida albicans; Antifungal; Microbiology; Antifungal drugs; Biology; Bacteria; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.001150972,0.0001719926,0.0002875202,0.0009682015,0.0004201057,0.0001404434,0.000602995,0.0001857991,0.000001871312],"category_scores_gemma":[0.001226546,0.0001065486,0.00006391872,0.002744988,0.003540219,0.0004131635,0.0002407491,0.001710751,0.000002655898],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001716223,"about_ca_system_score_gemma":0.0000703393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009095133,"about_ca_topic_score_gemma":0.00001713126,"domain_scores_codex":[0.9977715,0.00003161386,0.0004810035,0.0004445408,0.0005368391,0.0007345104],"domain_scores_gemma":[0.9986802,0.0007446179,0.00003976862,0.0002031351,0.0002237654,0.0001084913],"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":[0.00005277895,0.00006719176,0.0007036565,0.00005861426,0.00009393351,0.0001302318,0.00002119561,0.00007136201,0.3942508,0.01173132,0.0004250018,0.5923939],"study_design_scores_gemma":[0.0008433838,0.001326638,0.00299227,0.0007379862,0.00005255698,0.0008775101,0.002138413,0.01874862,0.4899081,0.4794576,0.002414676,0.0005022318],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9646435,0.003394858,0.000234311,0.03064054,0.000416241,0.000310026,0.00001740115,0.0002932428,0.0000498688],"genre_scores_gemma":[0.982959,0.01538698,0.001495119,0.000009864376,0.00005493709,0.00004506476,8.838169e-7,0.00001252812,0.00003557322],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5918917,"threshold_uncertainty_score":0.9991716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1038148170899919,"score_gpt":0.3941386280812065,"score_spread":0.2903238109912146,"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."}}