{"id":"W4379351702","doi":"10.2139/ssrn.4466598","title":"Design of Panel Experiments with Spatial and Temporal Interference","year":2023,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Spatial and Panel Data Analysis","field":"Economics, Econometrics and Finance","cited_by":12,"is_retracted":false,"has_abstract":false,"ca_institutions":"Quest University Canada","funders":"","keywords":"Interference (communication); Computer science; Telecommunications; Channel (broadcasting)","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":[0.01818071,0.002555548,0.003729259,0.001213867,0.001292537,0.001999689,0.002166365,0.003882215,0.01731678],"category_scores_gemma":[0.04727338,0.002104581,0.001999077,0.001227307,0.00210264,0.0009558967,0.00155245,0.003826192,0.002584332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001438702,"about_ca_system_score_gemma":0.002659376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005522923,"about_ca_topic_score_gemma":0.0005431579,"domain_scores_codex":[0.9783156,0.01198688,0.00157837,0.00417168,0.001971488,0.001975917],"domain_scores_gemma":[0.9597202,0.02423126,0.004282443,0.006754947,0.003405642,0.001605566],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"randomized_trial","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.4336775,0.06224493,0.01175121,0.00643341,0.003076926,0.0006244005,0.001879117,0.08121517,0.1558786,0.05764554,0.009003981,0.1765691],"study_design_scores_gemma":[0.2601691,0.2444198,0.03057489,0.0007452355,0.005739733,0.0004090275,0.0004369585,0.1414475,0.1156607,0.131967,0.06736988,0.001060158],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.29868,0.0007597837,0.4395761,0.0009617842,0.003049769,0.2376239,0.004035204,0.002157857,0.01315547],"genre_scores_gemma":[0.2232743,0.0003734045,0.2510495,0.001036419,0.0004338221,0.515411,0.001169755,0.0002334514,0.007018351],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01818071,"threshold_uncertainty_score":0.09614992,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06148843428090892,"score_gpt":0.2383185221609342,"score_spread":0.1768300878800253,"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."}}