{"id":"W6931071085","doi":"10.5281/zenodo.3873510","title":"cbinyu/pydeface: v2.0.4","year":2020,"lang":"fa","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Silicon Effects in Agriculture","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Concordia University","funders":"","keywords":"Process (computing); Identification (biology); Product (mathematics)","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","sts","scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005868663,0.0006006543,0.0005598658,0.00009347485,0.002956536,0.001788728,0.003035275,0.0005832004,0.3418711],"category_scores_gemma":[0.001058326,0.000315077,0.0002682371,0.001480685,0.0004101084,0.0001901255,0.002563965,0.001027967,0.1320242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002115893,"about_ca_system_score_gemma":0.00000344893,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006565404,"about_ca_topic_score_gemma":0.000003292565,"domain_scores_codex":[0.9954205,0.001064443,0.0004767008,0.001339283,0.0008321924,0.0008669333],"domain_scores_gemma":[0.9981323,0.00009845242,0.0003822049,0.0003809383,0.0003937367,0.0006123746],"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":[0.00004354534,0.0001660164,0.000004563344,0.0001068024,0.0001036755,0.00003707395,0.000370784,0.000006250598,0.02576247,0.001443494,0.810607,0.1613483],"study_design_scores_gemma":[0.0003679077,0.0007410103,0.001681097,0.0001610423,0.00005812702,0.000118347,0.0005257018,0.00005881515,0.0004183878,0.0000729566,0.9951473,0.0006492411],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.006844564,0.001072623,0.00004824795,0.007563581,0.0007668516,0.001860086,0.00174758,0.002525596,0.9775709],"genre_scores_gemma":[0.2703801,0.00351233,0.0006248438,0.005477036,0.01538221,6.46422e-7,0.0403814,0.008128348,0.6561131],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.3214578,"threshold_uncertainty_score":0.9999301,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03011074049895002,"score_gpt":0.2222288345324052,"score_spread":0.1921180940334551,"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."}}