{"id":"W2910804566","doi":"10.1111/amet.12735","title":"Data centers as infrastructural in‐betweens:","year":2019,"lang":"en","type":"article","venue":"American Ethnologist","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":51,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"American-Scandinavian Foundation; Wenner-Gren Foundation; American Council of Learned Societies; National Science Foundation","keywords":"Militarism; Cloud computing; Transformative learning; Landfall; Space (punctuation); Peninsula; History; Sociology; Archaeology; Political science; Geography; Computer science; Law; Politics; Meteorology","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00113618,0.0002450709,0.0001578505,0.001021172,0.008420706,0.005536191,0.0004784653,0.0004051478,0.005578264],"category_scores_gemma":[0.001192433,0.0001488198,0.00009422511,0.000954091,0.01327814,0.004168856,0.004601556,0.001230109,0.0002683416],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00597476,"about_ca_system_score_gemma":0.00344048,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03574122,"about_ca_topic_score_gemma":0.04354616,"domain_scores_codex":[0.9990718,0.000465698,0.00002506161,0.00008850541,0.00008527179,0.0002636751],"domain_scores_gemma":[0.9992411,0.0003108809,0.0001342632,0.00006587117,0.00009526897,0.0001525603],"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":[0.00007798315,0.00003583995,0.01204837,0.0001074718,0.000008839139,0.0005497828,0.3829602,0.0004717756,0.0004684629,0.5755528,0.008920925,0.01879753],"study_design_scores_gemma":[0.00001005435,0.00002903105,0.008081788,0.000389159,0.00001024789,0.000452333,0.5650754,0.0004656366,0.0004662534,0.0155456,0.4094564,0.00001801946],"study_design_candidate":"qualitative","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6933051,0.002719896,0.00324385,0.007536992,0.000173272,0.0000633111,0.0002141019,0.00004413922,0.2926994],"genre_scores_gemma":[0.9935781,0.0006382642,0.0002495973,0.0002505111,0.0000183482,0.00001655783,0.00001821143,0.00001015959,0.005220276],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03574122,"threshold_uncertainty_score":0.07106632,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03290704001681011,"score_gpt":0.2986533073082599,"score_spread":0.2657462672914498,"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."}}