{"id":"W4400094224","doi":"10.1080/10837450.2024.2372568","title":"Using chitosan-coated magnetite nanoparticles as a drug carrier for opioid delivery against breast cancer","year":2024,"lang":"en","type":"article","venue":"Pharmaceutical Development and Technology","topic":"Nanoparticle-Based Drug Delivery","field":"Materials Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"National Institute for Medical Research Development","keywords":"Chitosan; Drug delivery; Nanoparticle; Magnetite; Drug carrier; Magnetite Nanoparticles; Breast cancer; Drug; Materials science; Nanotechnology; Chemistry; Chemical engineering; Magnetic nanoparticles; Pharmacology; Cancer; Medicine; Organic chemistry; Internal 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":[0.00008971903,0.0002671617,0.000116444,0.0001582955,0.00009417292,0.0001601904,0.0001849508,0.0002422058,0.000477402],"category_scores_gemma":[0.00009212241,0.0001156518,0.0001616996,0.00009281902,0.0001352082,0.0001844239,0.0001399421,0.0001813005,0.0001404699],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003304642,"about_ca_system_score_gemma":0.0001926679,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001151889,"about_ca_topic_score_gemma":0.001966597,"domain_scores_codex":[0.999943,0.000006756727,0.000003961098,0.00001538995,0.00001668677,0.00001422723],"domain_scores_gemma":[0.9999605,0.000005901986,0.00001351749,0.000002901558,0.00001012292,0.000007082397],"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":[0.00004016428,0.00001002795,0.00003357189,0.00003782982,0.000003555856,0.00002665209,0.000005562488,0.00009443257,0.9980929,0.0000578075,0.00003042618,0.001566908],"study_design_scores_gemma":[0.00001119974,0.0002166363,0.0005034059,0.000003201968,0.00001666504,0.00008699656,0.000005337786,0.001448105,0.9961886,0.00001466002,0.001500439,0.0000048768],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848779,0.002652367,0.009512747,0.0001801082,0.00006110243,0.00007621207,0.00009987838,0.0001535983,0.002386024],"genre_scores_gemma":[0.9926857,0.0007991745,0.004447061,0.00004957497,0.00001157315,0.00002410919,0.00007093091,0.00001306583,0.001898823],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001151889,"threshold_uncertainty_score":0.002397716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02969609986099514,"score_gpt":0.3133953166944687,"score_spread":0.2836992168334736,"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."}}