{"id":"W1965221711","doi":"10.1108/02634501211262591","title":"e‐Marketing Ireland: cashing in on green dots","year":2012,"lang":"en","type":"article","venue":"Marketing Intelligence & Planning","topic":"Virtual Reality Applications and Impacts","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Marketing; Tourism; Business; Digital marketing; Originality; Marketing research; Return on marketing investment; Marketing strategy; Marketing management; Sociology","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":[0.007176416,0.0002337206,0.0002239347,0.0002917146,0.0002538515,0.0002314332,0.0008683656,0.0001085248,0.00002980222],"category_scores_gemma":[0.001510422,0.000225226,0.00006173793,0.0007362484,0.0000367014,0.0007872553,0.0002977659,0.0004751557,0.0001239096],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001485734,"about_ca_system_score_gemma":0.00004150904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003203898,"about_ca_topic_score_gemma":0.00001241115,"domain_scores_codex":[0.9973511,0.0004755981,0.000480771,0.0004420979,0.000392921,0.0008575913],"domain_scores_gemma":[0.9967747,0.002207932,0.0001854561,0.0005550772,0.00004297401,0.0002339053],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0001725422,0.0002394957,0.1537533,0.0001017178,0.00002418251,0.00005443632,0.01241344,0.004251039,0.0008705986,0.00845578,0.001088853,0.8185747],"study_design_scores_gemma":[0.0003571932,0.0001955676,0.7123256,0.003060514,0.00001674258,0.0001838887,0.002350659,0.2455868,0.003483185,0.001497306,0.02923422,0.001708369],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7182035,0.0005727439,0.2365885,0.0009622897,0.0004118213,0.0003235895,0.000003033101,0.000308992,0.04262551],"genre_scores_gemma":[0.9918314,0.00002321597,0.007169922,0.0005629293,0.0001753126,0.00002491608,0.000003787184,0.00001819103,0.0001903662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8168663,"threshold_uncertainty_score":0.9184449,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04663498315109519,"score_gpt":0.3148305284244973,"score_spread":0.2681955452734021,"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."}}