{"id":"W6969501615","doi":"10.5281/zenodo.8034444","title":"ttricco/sarracen: v1.1.0","year":2023,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Engineering and Material Science Research","field":"Materials Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Rendering (computer graphics); Interpolation (computer graphics); Normalization (sociology); Linear interpolation; Bilinear interpolation; Nearest-neighbor interpolation","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":["scholarly_communication","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.001096161,0.0002193131,0.00023979,0.0004872601,0.001004863,0.001123319,0.001668622,0.0001778579,0.09931564],"category_scores_gemma":[0.0007223128,0.000212747,0.00005716857,0.0007532134,0.0002133694,0.0001359105,0.001322262,0.0002646984,0.1392997],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001672141,"about_ca_system_score_gemma":0.000007015847,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001567897,"about_ca_topic_score_gemma":0.000002262788,"domain_scores_codex":[0.9975609,0.0002225254,0.0002191057,0.0006107322,0.000702337,0.0006843981],"domain_scores_gemma":[0.9987903,0.00002552228,0.0001100216,0.0006224062,0.0001819808,0.0002697249],"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":[0.000008875106,0.00003263748,1.075936e-7,0.000100254,0.00001069623,0.00002279335,0.0001102652,0.00002301081,0.03252958,0.0009603953,0.9519967,0.01420466],"study_design_scores_gemma":[0.0001696867,0.00008358775,0.0000155161,0.0001059364,0.000006826712,0.00003002666,0.00005377118,0.00004758857,0.001647251,0.00004130678,0.9975554,0.0002430387],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004384457,0.0001968611,0.001205783,0.000376013,0.001044849,0.000563877,0.0007413578,0.009403216,0.9860296],"genre_scores_gemma":[0.01068517,0.001125419,0.0009758263,0.00008549193,0.001896061,3.343328e-7,0.001339352,0.03919619,0.9446961],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.04555874,"threshold_uncertainty_score":0.9999136,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03486459308782267,"score_gpt":0.2593705860731836,"score_spread":0.224505992985361,"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."}}