{"id":"W4285493440","doi":"10.5731/pdajpst.2021.012726","title":"Challenges Encountered in the Implementation of Bio-Fluorescent Particle Counting Systems as a Routine Microbial Monitoring Tool","year":2022,"lang":"en","type":"article","venue":"PDA Journal of Pharmaceutical Science and Technology","topic":"Biosensors and Analytical Detection","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Pfizer (Canada)","funders":"","keywords":"Bioburden; Autofluorescence; Fluorescence; Process engineering; Computer science; Continuous monitoring; Nanotechnology; Biochemical engineering; Environmental science; Materials science; Biology; Engineering; Microbiology; Operations management; Physics","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":[0.06792857,0.0007682615,0.0010667,0.001285311,0.001783895,0.009512583,0.005283341,0.004044444,0.001653578],"category_scores_gemma":[0.05148118,0.0007097634,0.0006433958,0.001254283,0.003038362,0.005259897,0.003914078,0.004442956,0.001908744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002712928,"about_ca_system_score_gemma":0.008483759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005553179,"about_ca_topic_score_gemma":0.005970924,"domain_scores_codex":[0.9458932,0.0211639,0.003844461,0.003319268,0.02348725,0.002292028],"domain_scores_gemma":[0.9436189,0.01771744,0.004500966,0.003787501,0.02869901,0.001676128],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003871761,0.0006243662,0.01287692,0.004075491,0.0001183541,0.001362456,0.005508442,0.01093913,0.08337501,0.0330367,0.01921861,0.8284773],"study_design_scores_gemma":[0.00009631745,0.003732066,0.01764878,0.006200737,0.0002001641,0.005754536,0.02517214,0.03574274,0.1246483,0.0397672,0.7404423,0.0005947223],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1248988,0.03334537,0.6444391,0.1481954,0.003889225,0.002150854,0.0003306831,0.002253039,0.04049769],"genre_scores_gemma":[0.3220476,0.01723525,0.6364051,0.01188229,0.0008959728,0.0009683795,0.0002685487,0.0003185821,0.009978217],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.06792857,"threshold_uncertainty_score":0.3592449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02896371485864085,"score_gpt":0.3203416961468228,"score_spread":0.2913779812881819,"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."}}