{"id":"W2770526968","doi":"10.21307/ijssis-2017-836","title":"Standard Arpu Calculation Improvement Using Artificial Intelligent Techniques","year":2015,"lang":"en","type":"article","venue":"International Journal on Smart Sensing and Intelligent Systems","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Algonquin College","funders":"","keywords":"Computer science; Revenue; Duration (music); Quality (philosophy); Service (business); Software","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":[0.001322302,0.0008649498,0.0007784001,0.00161408,0.000456723,0.001487994,0.001609826,0.0008067979,0.00425264],"category_scores_gemma":[0.007250796,0.0003656693,0.000666204,0.001041225,0.0004003265,0.00112429,0.0009545535,0.0008496877,0.00157681],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005557233,"about_ca_system_score_gemma":0.0006773288,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00343729,"about_ca_topic_score_gemma":0.00248208,"domain_scores_codex":[0.9989016,0.0002610433,0.00009403967,0.0002551115,0.0004147876,0.00007340823],"domain_scores_gemma":[0.997614,0.0009694319,0.0002400729,0.0005298259,0.0006056303,0.00004095464],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003123535,0.000265874,0.006243661,0.0002723172,0.0001002084,0.0002789987,0.0003519511,0.4180034,0.01835293,0.0185791,0.006196287,0.5310429],"study_design_scores_gemma":[0.000005855466,0.0000254851,0.0005367434,0.00000931454,0.000006125623,0.00004769146,0.00001942506,0.9915453,0.003667949,0.002170552,0.001954619,0.00001103823],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02245318,0.0001078472,0.9693899,0.0001081263,0.00007258262,0.00006980095,0.00007762546,0.003910031,0.003810923],"genre_scores_gemma":[0.4572978,0.0001266968,0.5370341,0.00007884341,0.00004227063,0.0001965945,0.0002219752,0.0005876562,0.004414121],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00425264,"threshold_uncertainty_score":0.0142265,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05643143567596925,"score_gpt":0.3092453448279224,"score_spread":0.2528139091519531,"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."}}