{"id":"W3092617015","doi":"10.5210/spir.v2020i0.11197","title":"TWITTERING RESEARCH, CALLING OUT AND CANCELING CULTURES: A STORY ANDSOME QUESTIONS","year":2020,"lang":"en","type":"article","venue":"AoIR Selected Papers of Internet Research","topic":"Social Media and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Context (archaeology); Social media; Sociology; Public relations; Set (abstract data type); Government (linguistics); Hegemony; Media studies; Event (particle physics); Sustainability; Political science; Computer science; Politics; History","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":[],"consensus_categories":[],"category_scores_codex":[0.001629643,0.0001031563,0.0002085386,0.0001912261,0.0006306855,0.0001173439,0.0004232379,0.0001763349,0.0001121411],"category_scores_gemma":[0.007858013,0.0001016804,0.00004093607,0.000972149,0.001196661,0.0001140296,0.0001503135,0.001280747,0.00002333007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002394729,"about_ca_system_score_gemma":0.0007392974,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01595186,"about_ca_topic_score_gemma":0.008041859,"domain_scores_codex":[0.9960839,0.001419458,0.0002144366,0.0003253877,0.001125875,0.0008310152],"domain_scores_gemma":[0.9966741,0.001548665,0.00004270986,0.0001173438,0.00114179,0.0004754053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"qualitative","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001560132,0.00007457418,0.01983598,0.0002344442,0.0001375955,0.00004390093,0.8352672,0.00001468787,0.105933,0.01451995,0.01890747,0.00487512],"study_design_scores_gemma":[0.001071212,0.001181739,0.003357655,0.0008918067,0.00003162455,0.000003338252,0.3515388,0.0006654011,0.01948025,0.001529009,0.6196179,0.0006312568],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9753315,0.001329323,0.00002194157,0.007949115,0.0001668689,0.0003732864,0.000008925874,0.0000836968,0.01473532],"genre_scores_gemma":[0.9965369,0.001022196,0.0001747564,0.0001643522,0.0007078745,0.00003747757,0.00000494319,0.00001910404,0.001332466],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.6007104,"threshold_uncertainty_score":0.990601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1418461978647468,"score_gpt":0.4546442962165489,"score_spread":0.3127980983518021,"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."}}