{"id":"W4232225786","doi":"10.26522/ti.v2i1.715","title":"Screen shot 19","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; Computer graphics (images); Materials science","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":["insufficient_payload"],"consensus_categories":["insufficient_payload"],"category_scores_codex":[0.0005988431,0.001528234,0.001180622,0.002354328,0.0009058499,0.00251645,0.001407668,0.00103327,0.7787483],"category_scores_gemma":[0.003616156,0.001062771,0.001194464,0.001921492,0.0002423336,0.001359326,0.001883176,0.0009614281,0.5531461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005521551,"about_ca_system_score_gemma":0.000816624,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006387758,"about_ca_topic_score_gemma":0.01280748,"domain_scores_codex":[0.9996355,0.00003719936,0.00001990865,0.00007776634,0.0001430407,0.00008666274],"domain_scores_gemma":[0.9984749,0.0003857989,0.00005501075,0.000367452,0.0004853045,0.0002316388],"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":[0.0002270937,0.00003271981,0.0003597729,0.0001497932,0.00001920778,0.00006250075,0.00003828133,0.0001451963,0.0008432695,0.0005417363,0.9809148,0.0166656],"study_design_scores_gemma":[0.0004162502,0.00005679659,0.005243069,0.00018628,0.00004953263,0.0001807364,0.00008316716,0.002963749,0.004569577,0.004319289,0.9818272,0.00010432],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"other","genre_scores_codex":[0.003620001,0.000306268,0.02712449,0.0006589409,0.001345251,0.0004945199,0.5207682,0.2874633,0.158219],"genre_scores_gemma":[0.02306962,0.0004573414,0.04395388,0.001280831,0.0005808122,0.001320527,0.5175584,0.1712514,0.2405273],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.2212517,"threshold_uncertainty_score":0.3155887,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0788408454332446,"score_gpt":0.2068509599946387,"score_spread":0.1280101145613941,"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."}}