{"id":"W2751825420","doi":"10.5281/zenodo.887933","title":"reiinakano/scikit-plot: v0.2.8","year":2017,"lang":"en","type":"article","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Digital Imaging for Blood Diseases","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Lab_Bell (Canada)","funders":"","keywords":"Plot (graphics); Confusion; Mathematics; Projection (relational algebra); Scatter plot; Statistics; Confusion matrix; Artificial intelligence; Computer science; Algorithm; Psychology","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":["sts","scholarly_communication","open_science","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0004268586,0.0001548798,0.0001363542,0.0001671156,0.004434592,0.007965142,0.005398264,0.00003779992,0.001019354],"category_scores_gemma":[0.00134582,0.0001642105,0.00007358836,0.000230109,0.0002813389,0.002164816,0.00463259,0.0001692712,0.01342646],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007417073,"about_ca_system_score_gemma":0.000006860574,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001762007,"about_ca_topic_score_gemma":1.534373e-7,"domain_scores_codex":[0.9981987,0.0001102001,0.0001987551,0.0005608373,0.0004751474,0.0004563493],"domain_scores_gemma":[0.9971449,0.00001630377,0.0001632676,0.0019017,0.0004845813,0.0002892142],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002292304,0.0003242161,0.0000300385,0.00004892924,0.00004880973,0.000108516,0.0005910267,0.00001942627,0.001329042,0.1396746,0.3741379,0.4836646],"study_design_scores_gemma":[0.0003990523,0.0001174641,0.002936158,0.00002688031,0.000007789709,0.0001039621,0.00002706254,0.001110745,0.0007687996,0.003353916,0.9909241,0.0002241145],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.01220849,0.0001238807,0.03331771,0.005429569,0.0004245588,0.0004328412,0.0001339122,0.003430096,0.944499],"genre_scores_gemma":[0.9918184,0.00002336029,0.002618804,0.0003365747,0.0001609986,4.152175e-8,0.000191281,0.0009251272,0.003925378],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.97961,"threshold_uncertainty_score":0.999983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04126708364206683,"score_gpt":0.2597810084174828,"score_spread":0.2185139247754159,"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."}}