{"id":"W3185556861","doi":"10.29363/nanoge.eimc.2021.048","title":"Inlaid Microfluidics for In Situ Phosphate Sensing","year":2021,"lang":"en","type":"article","venue":"","topic":"Analytical Chemistry and Sensors","field":"Chemical Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Dalhousie University","funders":"","keywords":"Microfluidics; In situ; Nanotechnology; Phosphate; Materials science; Computer science; Chemistry","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":[0.0004796553,0.0005264038,0.0003652655,0.0004672105,0.0005057253,0.001122685,0.001058196,0.0006632218,0.004031511],"category_scores_gemma":[0.0006163098,0.0004390213,0.0002206377,0.0002314581,0.000410261,0.0009816384,0.001168692,0.0007909852,0.001511358],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007480308,"about_ca_system_score_gemma":0.0006357291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005662506,"about_ca_topic_score_gemma":0.002031385,"domain_scores_codex":[0.9995278,0.00005907272,0.00003170075,0.0001197302,0.000185934,0.00007587705],"domain_scores_gemma":[0.9997451,0.00007685293,0.00006422569,0.00002920198,0.00005516694,0.00002946303],"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":[0.0001138226,0.00006342326,0.0002456594,0.000216236,0.00001171178,0.00009147262,0.00009871533,0.0002031208,0.9619072,0.00500854,0.004018383,0.02802161],"study_design_scores_gemma":[0.00001844905,0.0001433193,0.000357573,0.00002355047,0.00001410308,0.0002038299,0.00004035295,0.005177966,0.9584363,0.0005784234,0.03497451,0.00003179045],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4326417,0.03294906,0.4538666,0.005786241,0.005729087,0.0004820153,0.003075662,0.006985153,0.05848442],"genre_scores_gemma":[0.7005329,0.00770567,0.2425928,0.002110062,0.0005833324,0.0004037909,0.001158152,0.0002052822,0.04470798],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004031511,"threshold_uncertainty_score":0.01348674,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01503250537332535,"score_gpt":0.2384507657738478,"score_spread":0.2234182604005224,"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."}}