{"id":"W6983783631","doi":"","title":"A novel method to detect label-free nanoplastics within whole organisms using enhanced dark field hyperspectral imaging","year":2024,"lang":"en","type":"dissertation","venue":"eScholarship@McGill (McGill)","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fisheries and Oceans Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; McGill University","keywords":"Hyperspectral imaging; Field (mathematics); Dark field microscopy; Feature (linguistics)","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":[0.0003256897,0.0005655495,0.0001707723,0.0006336576,0.0002961386,0.0004422185,0.0006530324,0.0007397351,0.001492661],"category_scores_gemma":[0.0002252582,0.0004252882,0.0002689299,0.0002460378,0.000475439,0.000673229,0.0006529363,0.001081707,0.0006661552],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004543566,"about_ca_system_score_gemma":0.0003446373,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001017963,"about_ca_topic_score_gemma":0.003025612,"domain_scores_codex":[0.9997413,0.00002470288,0.00001142524,0.00009381806,0.0001054394,0.00002326096],"domain_scores_gemma":[0.9997457,0.00006168964,0.00007203692,0.00003309954,0.00005991689,0.0000276557],"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":[0.000006448894,0.00001361298,0.0001026475,0.00004749472,0.000002875412,0.00002468286,0.00001266912,0.00007783857,0.9947051,0.000147843,0.0001189979,0.00473988],"study_design_scores_gemma":[0.000005483028,0.00007402003,0.001735412,0.000009704835,0.000009391584,0.0003447421,0.00002435876,0.005325419,0.9877226,0.000116134,0.00461203,0.00002056054],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2953148,0.002088808,0.6902627,0.001079939,0.0002263659,0.0002840977,0.0006311578,0.001814326,0.008297707],"genre_scores_gemma":[0.3197303,0.00193475,0.6660393,0.0005207954,0.0000533206,0.0003656382,0.000461776,0.0001154953,0.01077852],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001492661,"threshold_uncertainty_score":0.004993439,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01191886763613673,"score_gpt":0.248298562914859,"score_spread":0.2363796952787222,"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."}}