{"id":"W2622343989","doi":"","title":"Representação: construindo as diferenças em Rocks at Whiskey Trench","year":2016,"lang":"pt","type":"article","venue":"Faces da História","topic":"Radio, Podcasts, and Digital Media","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Historiography; Representation (politics); Humanities; Art; Trench; Art history; Political science; History; Archaeology; Law; Materials science; Politics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008939596,0.0003322737,0.0002063928,0.002277893,0.007880303,0.008206677,0.0007975879,0.0008485023,0.01154799],"category_scores_gemma":[0.003208874,0.0001879895,0.0001437204,0.0036106,0.00929457,0.002697545,0.003510511,0.001326802,0.0003540424],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01588843,"about_ca_system_score_gemma":0.008400151,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.5600734,"about_ca_topic_score_gemma":0.7088296,"domain_scores_codex":[0.9987888,0.0003047799,0.00003291247,0.0001392549,0.000450135,0.0002841528],"domain_scores_gemma":[0.9986369,0.0004106327,0.0002242734,0.0001026968,0.0003696769,0.0002558093],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"qualitative","study_design_scores_codex":[0.0001018222,0.00001348947,0.01058955,0.0001745193,0.000009595401,0.0006867983,0.8089473,0.0003194878,0.002414624,0.1483629,0.004465919,0.02391405],"study_design_scores_gemma":[0.000006778126,0.00002971476,0.03866593,0.0002732339,0.00002577489,0.000436816,0.707983,0.000477343,0.000992945,0.005152,0.2459213,0.00003515682],"study_design_candidate":"qualitative","study_design_consensus":"qualitative","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6722175,0.0009941761,0.002714647,0.003035141,0.0001083953,0.00005404675,0.0003517602,0.00005523258,0.3204691],"genre_scores_gemma":[0.980631,0.0003923253,0.000623835,0.0000537694,0.00001196166,0.00001127651,0.00008625133,0.00002671819,0.01816292],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5600734,"threshold_uncertainty_score":0.8850349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04992627739328982,"score_gpt":0.3120300053237909,"score_spread":0.2621037279305011,"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."}}