{"id":"W4404459247","doi":"10.1039/d4em00605d","title":"An introduction to machine learning tools for the analysis of microplastics in complex matrices","year":2024,"lang":"en","type":"review","venue":"Environmental Science Processes & Impacts","topic":"Microplastics and Plastic Pollution","field":"Environmental Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"National Research Council Canada; Government of Canada","keywords":"Microplastics; Environmental science; Environmental chemistry; Environmental engineering; Chemistry","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":[0.001508393,0.001736466,0.001356216,0.00309341,0.0003392433,0.001663196,0.001519153,0.002056893,0.006770444],"category_scores_gemma":[0.003449386,0.0007733963,0.001497541,0.003473093,0.00101012,0.002430654,0.00103134,0.004466289,0.005918711],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007793754,"about_ca_system_score_gemma":0.0009399166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001396683,"about_ca_topic_score_gemma":0.001444593,"domain_scores_codex":[0.9990114,0.0002032259,0.000127271,0.0001962325,0.0004182255,0.00004359153],"domain_scores_gemma":[0.9975142,0.001757015,0.0001403581,0.00009956474,0.0004203161,0.00006852278],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00004494682,0.0001340069,0.000480425,0.008381994,0.0002130774,0.0002330858,0.000115019,0.007326738,0.004722151,0.02464447,0.0633911,0.8903131],"study_design_scores_gemma":[0.00001917091,0.0001760364,0.001288287,0.003341992,0.00008757705,0.0008435333,0.00005784709,0.01263773,0.003391816,0.04034589,0.9376689,0.000141231],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.0009012373,0.7066939,0.2673758,0.004291298,0.003149692,0.0001839489,0.0008824457,0.002051742,0.01446986],"genre_scores_gemma":[0.009183851,0.7622436,0.2080048,0.002428753,0.004723742,0.000507652,0.001231331,0.0004054708,0.01127086],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006770444,"threshold_uncertainty_score":0.02264935,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0290063311443191,"score_gpt":0.3110751603564189,"score_spread":0.2820688292120997,"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."}}