{"id":"W4382651670","doi":"10.1002/admi.202300269","title":"Learning from Nature: Fighting Pathogenic <i>Escherichia coli</i> Bacteria Using Nanoplasmonic Metasurfaces","year":2023,"lang":"en","type":"article","venue":"Advanced Materials Interfaces","topic":"Polydiacetylene-based materials and applications","field":"Chemistry","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Royal Military College of Canada; Queen's University","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Foundation for Innovation","keywords":"Materials science; Escherichia coli; Photothermal therapy; Nanotechnology; Azobenzene; Nanostructure; Bacteria; Nanoparticle; Optoelectronics; Chemistry; Polymer; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003186007,0.0004846382,0.0006559596,0.00007566767,0.0004055048,0.0003361538,0.0005212461,0.0003503636,0.002858324],"category_scores_gemma":[0.000168597,0.0004699757,0.00009693017,0.0003105236,0.00009174745,0.0003991483,0.000317997,0.0003384417,0.0004480788],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009716022,"about_ca_system_score_gemma":0.00007061665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001242639,"about_ca_topic_score_gemma":0.00001310223,"domain_scores_codex":[0.9973919,0.0001120268,0.0007325021,0.0007780119,0.0002681408,0.0007173878],"domain_scores_gemma":[0.9984729,0.0002631164,0.0005155476,0.0005434703,0.00007673814,0.0001281705],"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":[0.0001074997,0.00002911979,0.00005860697,0.0001159182,0.00009537172,0.000008618316,0.0001455749,0.001367841,0.9975039,0.00005899288,0.0000617563,0.0004467903],"study_design_scores_gemma":[0.000529773,0.00002629841,0.0001206876,0.0002559843,0.00008851154,0.000003218084,0.0003459471,0.0002910014,0.9896262,0.0004837012,0.007703829,0.0005247959],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9957937,0.000689731,0.00004254637,0.00008665304,0.001224531,0.0001779937,0.0008045638,0.00086495,0.0003153154],"genre_scores_gemma":[0.9901624,0.0004728627,0.00765284,0.00009078115,0.0002093402,0.0001414284,0.0005691737,0.000128539,0.0005726185],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007877658,"threshold_uncertainty_score":0.9997752,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01584685338306858,"score_gpt":0.2627648378564242,"score_spread":0.2469179844733557,"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."}}