{"id":"W4251726153","doi":"10.26522/ti.v2i1.710","title":"Screen shot 14","year":2013,"lang":"en","type":"article","venue":"ti<","topic":"Diverse Scientific and Economic Studies","field":"Economics, Econometrics and Finance","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Shot (pellet); Computer science; Materials science; Metallurgy","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0001638884,0.0000686226,0.0001695205,0.00007420179,0.00007699311,0.00007662188,0.0001543431,0.00003108363,0.06707095],"category_scores_gemma":[0.00002607001,0.00007475557,0.00005657411,0.00007110491,0.00005639545,0.0002019093,0.00007228036,0.0000418586,0.2861317],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002712054,"about_ca_system_score_gemma":0.000003100113,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000473713,"about_ca_topic_score_gemma":0.000005585819,"domain_scores_codex":[0.9993376,0.000001854742,0.0002129546,0.0002376643,0.00001240504,0.0001974887],"domain_scores_gemma":[0.9996428,0.00001210293,0.00007475723,0.0002038717,0.00001374434,0.00005267053],"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":[0.000001047467,0.00001898296,0.01041319,0.000003034049,0.00003064488,5.010667e-7,0.0002270399,0.000006244453,0.000005076488,0.1133299,0.8749952,0.0009691177],"study_design_scores_gemma":[0.0002574333,0.00001408874,0.02325167,0.000002839909,0.000002025509,7.57683e-7,0.0002053285,0.0004996757,0.00002271159,0.01572634,0.9598328,0.0001843152],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.03715989,0.0004143786,0.00008099731,0.0004055523,0.0009874515,0.00009949531,0.00008469033,0.00003636265,0.9607312],"genre_scores_gemma":[0.4888418,0.00004778949,0.0003104171,0.0004345721,0.00009938672,0.00001687334,0.000005836579,0.000008737905,0.5102347],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.4516819,"threshold_uncertainty_score":0.9337819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06907756777686751,"score_gpt":0.2013940170147465,"score_spread":0.1323164492378791,"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."}}