{"id":"W4247193665","doi":"10.1515/iupac.83.0435","title":"Plate Reader","year":2016,"lang":"en","type":"dataset","venue":"IUPAC Standards Online","topic":"Computational Drug Discovery Methods","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Glossary; Field (mathematics); Context (archaeology); Process (computing); Computer science; Multidisciplinary approach; Data science; Component (thermodynamics); Management science; Engineering; Sociology; Linguistics; Biology; Mathematics; Social science","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00111524,0.0004640097,0.0005659005,0.0003363291,0.0001197581,0.000245727,0.00211275,0.0002866681,0.0005591879],"category_scores_gemma":[0.0006145578,0.0003592086,0.0002041297,0.0004052975,0.0001119651,0.0004501248,0.0009574873,0.000480023,0.00001235748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00041703,"about_ca_system_score_gemma":0.001517182,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004526837,"about_ca_topic_score_gemma":0.00007386204,"domain_scores_codex":[0.9960963,0.0002856888,0.0005307032,0.0008978189,0.001686346,0.0005031258],"domain_scores_gemma":[0.9968167,0.0005494104,0.000311451,0.001622072,0.0004963119,0.0002040372],"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":[0.0000226857,0.00008603201,6.622399e-7,0.0000449524,0.0000613032,0.00009653727,0.00001420703,0.0001252688,0.000001892557,0.0006725732,0.9800701,0.01880377],"study_design_scores_gemma":[0.000474869,0.0000873719,0.00003393584,0.0002225949,0.00002442676,0.00004145677,0.000002154815,0.00102279,0.00001593713,0.006994074,0.9906021,0.0004783128],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.000007571052,0.0002694665,0.2243167,0.001617435,0.001439579,0.0001649028,0.7719903,0.0001307694,0.00006322917],"genre_scores_gemma":[0.000001819839,0.0001959698,0.01179911,0.0006761251,0.0008037352,0.00001252669,0.9861253,0.00002724817,0.0003580912],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.2141351,"threshold_uncertainty_score":0.999886,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02567590193249468,"score_gpt":0.4320207778990955,"score_spread":0.4063448759666008,"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."}}