{"id":"W6887786960","doi":"10.17612/p7201q","title":"Statistically Generated Medium","year":2016,"lang":"en","type":"dataset","venue":"Digital Rocks Portal","topic":"","field":"","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Statistical analysis; Section (typography); Pattern recognition (psychology); Set (abstract data type); Noise (video)","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","insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001418771,0.0009489521,0.0008581235,0.0003678241,0.0001132928,0.0006220794,0.0009810444,0.0006450701,0.005932732],"category_scores_gemma":[0.001295186,0.0007466644,0.0002525674,0.0003087389,0.0002733727,0.0007106884,0.0004567778,0.0006100343,0.06230513],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001516814,"about_ca_system_score_gemma":0.0008472328,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006119339,"about_ca_topic_score_gemma":0.0002198837,"domain_scores_codex":[0.9952996,0.00003938426,0.0009971032,0.001109283,0.001460019,0.00109459],"domain_scores_gemma":[0.9968992,0.0002000737,0.0005689578,0.00125585,0.0003534321,0.0007224721],"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":[0.00007202117,0.0002079654,0.00003575388,0.00004644758,0.0002444963,0.002340478,0.000003108948,0.00000118023,0.00003628198,0.000023808,0.996187,0.0008015133],"study_design_scores_gemma":[0.0005940255,0.0001435882,0.00005493657,0.0001156581,0.0001251163,0.000197989,0.000006176899,0.000003276611,0.00005894095,0.0002846841,0.9973677,0.001047934],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0000578738,0.00007892465,0.0002307857,0.00003095432,0.001071798,0.0003611385,0.990869,0.0003340206,0.006965464],"genre_scores_gemma":[0.0007959391,0.00002107941,0.00002449063,0.0001351399,0.001176653,0.0000576137,0.9940079,0.00025573,0.003525444],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.05637239,"threshold_uncertainty_score":0.9994984,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01269504417537724,"score_gpt":0.2621438206269835,"score_spread":0.2494487764516062,"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."}}