{"id":"W4402961343","doi":"10.54097/jpavb546","title":"Addressing cold start problems in new store locations with transfer learning in spatial GNNs","year":2024,"lang":"en","type":"article","venue":"Journal of Computing and Electronic Information Management","topic":"IoT-based Smart Home Systems","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Transfer of learning; Transfer (computing); Artificial intelligence","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":[0.0005999894,0.00009823679,0.000141483,0.0005611508,0.00004262616,0.0001492485,0.0000594454,0.00003132826,0.000003523828],"category_scores_gemma":[0.000002760963,0.0000875802,0.00002263195,0.0003155221,0.000007723604,0.0004464665,0.00000830751,0.0004296154,0.000003299273],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003299133,"about_ca_system_score_gemma":0.0001190733,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000422037,"about_ca_topic_score_gemma":0.000190899,"domain_scores_codex":[0.9990004,0.00002632197,0.0004817806,0.00004867578,0.0001962756,0.0002465655],"domain_scores_gemma":[0.9998245,0.00002469817,0.00004385845,0.00004306946,0.00002741855,0.00003650009],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008732097,0.000004791663,0.000670243,0.0005974416,0.00004034801,0.00000554065,0.003761782,0.9591109,0.00001976526,0.001599872,0.0001934519,0.03398709],"study_design_scores_gemma":[0.001435407,0.0002538433,0.004433313,0.00230631,0.00003194937,0.0000474438,0.001295334,0.9584337,0.00007899966,0.00007045874,0.03140314,0.0002100536],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3575903,0.0007951803,0.6395282,0.0001388123,0.0002154661,0.0002612751,3.065804e-7,0.00008175871,0.001388747],"genre_scores_gemma":[0.9994523,0.00007957604,0.0003245562,0.00001616803,0.00007070065,0.000001775317,0.000003253093,0.00001048774,0.00004117301],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.641862,"threshold_uncertainty_score":0.3571417,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007721039573158409,"score_gpt":0.2105927574984079,"score_spread":0.2028717179252494,"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."}}