{"id":"W4383906372","doi":"10.26434/chemrxiv-2023-3rcmh-v2","title":"WITHDRAWN","year":2023,"lang":"en","type":"preprint","venue":"ChemRxiv","topic":"Innovative Microfluidic and Catalytic Techniques Innovation","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Killam Trusts; Canada Foundation for Innovation; Pfizer","keywords":"Computer science; Automation; Software; Visualization; Data acquisition; Instrument control; Data collection; Workflow; Real-time computing; Artificial intelligence; Computer hardware; Engineering","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.002765396,0.0009117819,0.0008673493,0.001982622,0.002660295,0.00685882,0.001600367,0.003479647,0.4275419],"category_scores_gemma":[0.02594702,0.000492963,0.001028716,0.002045229,0.001430567,0.002747604,0.002397929,0.005300426,0.3841904],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002870903,"about_ca_system_score_gemma":0.004878354,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004107208,"about_ca_topic_score_gemma":0.004142015,"domain_scores_codex":[0.996331,0.0004344272,0.00031719,0.0005306806,0.002072985,0.0003136962],"domain_scores_gemma":[0.9908351,0.001478182,0.0003892628,0.001431494,0.005093284,0.0007726549],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001056003,0.00001120577,0.000198039,0.0002153742,0.00001510701,0.0002974943,0.00007415126,0.00002525677,0.0006916293,0.006113038,0.9574955,0.03475763],"study_design_scores_gemma":[0.00001226563,0.000008365266,0.0002149345,0.00006629385,0.000006715797,0.000259285,0.00003623442,0.00002118641,0.0003567027,0.001026642,0.9979831,0.00000813352],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.003129407,0.008906856,0.007081996,0.09986521,0.4118758,0.0007420142,0.04218558,0.004896635,0.4213165],"genre_scores_gemma":[0.01014309,0.004633542,0.002318594,0.02690044,0.0167989,0.0002251621,0.01389422,0.002065265,0.9230207],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.5724581,"threshold_uncertainty_score":0,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02749174551781075,"score_gpt":0.2554018330290105,"score_spread":0.2279100875111997,"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."}}