{"id":"W4413417583","doi":"10.4324/9781003584827-5","title":"Hyper Visibility and Invisibility","year":2025,"lang":"en","type":"book-chapter","venue":"","topic":"Media Studies and Communication","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Invisibility; Visibility; Geography; Computer science; Artificial intelligence; Meteorology","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":[0.005390879,0.0004038816,0.0004047424,0.00322889,0.01004003,0.0266518,0.001362667,0.001974494,0.008411339],"category_scores_gemma":[0.02177195,0.0004118373,0.0003364384,0.002564619,0.04768457,0.01391435,0.009576688,0.004159286,0.0008079188],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008342071,"about_ca_system_score_gemma":0.008342375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03623795,"about_ca_topic_score_gemma":0.02772216,"domain_scores_codex":[0.9911669,0.0030851,0.000259278,0.0006938007,0.003621079,0.001173863],"domain_scores_gemma":[0.9822357,0.01081995,0.001459391,0.001951694,0.002171846,0.001361385],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"qualitative","study_design_scores_codex":[0.00005354096,0.00002061776,0.002167612,0.0002575243,0.00001032747,0.0006766543,0.2320895,0.0001017345,0.001952468,0.720504,0.004012048,0.03815392],"study_design_scores_gemma":[0.0000255408,0.00007242741,0.007130456,0.001301221,0.00005082519,0.001627499,0.1520949,0.0002906298,0.0022414,0.3296177,0.5054759,0.00007158395],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"other","genre_gemma":"empirical","genre_scores_codex":[0.1009197,0.01047093,0.008600223,0.01360557,0.0006325144,0.00006840628,0.0000628136,0.0001589835,0.8654807],"genre_scores_gemma":[0.957355,0.003839653,0.001691763,0.001131276,0.0004318564,0.00005464387,0.00004855661,0.0001297494,0.03531758],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03623795,"threshold_uncertainty_score":0.07205403,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0425593168411157,"score_gpt":0.3242612235658034,"score_spread":0.2817019067246877,"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."}}